WDR-5 exhibits H3K4 methylation-independent activity during embryonic development in C. elegans

WDR-5 exhibits H3K4 methylation-independent activity during embryonic development in C. elegans | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article WDR-5 exhibits H3K4 methylation-independent activity during embryonic development in C. elegans Nurulhafizah Binti Samsudin, Kate Fisher, Gino B Poulin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7240678/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Mar, 2026 Read the published version in Epigenetics & Chromatin → Version 1 posted 11 You are reading this latest preprint version Abstract Background Histone H3 lysine 4 methylation (H3K4me) is generally associated with active transcription and bivalent chromatin, but can also contribute to repression. In metazoans, H3K4 methylation is catalysed by KMT2 methyltransferases assembled with the core scaffolding proteins WDR5, ASH2L, and RBBP5. RBBP5 mediates complex assembly and nucleosome binding, whilst WDR5 stabilises interactions to promote tri-methylation. However, WDR5 also exhibits additional ‘moonlighting’ functions, leaving its specific roles in H3K4 methylation and transcription regulation unclear. Using C. elegans embryos, spike-in ChIP-seq, and null alleles of wdr-5(-) and rbbp-5(-) , we dissected the contributions of these scaffolds towards H3K4 mono-, di-, and tri-methylation as well as gene expression during C. elegans embryogenesis. Results We show that C. elegans RBBP-5 is essential for both mono- and multi-methylated H3K4 deposition. On the other hand, WDR-5 is primarily required for H3K4me3, but can influence H3K4me2 and H3K4me1 deposition either positively or negatively depending on the genomic feature involved. We additionally performed RNA-seq on these mutants and found that rbbp-5 deletion was largely tolerated with mis-regulation of ~ 700 genes, whereas the wdr-5 deletion led to widespread transcriptomic disruption (~ 3000 genes). We initially hypothesised that these broad changes were driven by the altered H3K4me1 and H3K4me2 landscapes in the wdr-5(-) mutant. However, transcriptomic profiling of the wdr-5(-); rbbp-5(-) double mutant, which lacks H3K4 methylation, revealed a high degree of similarity to the wdr-5(-) single mutant. This refuted our initial hypothesis and indicates that the changes in H3K4 methylation are unlikely to underlie the transcriptional effects of the wdr-5 deletion. Conclusions Our findings strongly indicate that WDR-5 profoundly shapes gene expression through mechanisms beyond H3K4 methylation. Distinguishing between H3K4me-dependent and independent functions of WDR-5 will further understanding of its roles in development and disease. Chromatin H3K4 methylation MLL/SET/COMPASS complex chromosome X WDR-5 RBBP-5 C. elegans embryo Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Background The chromatin landscape is shaped by the organisation of nucleosomes within the confined space of the nucleus. The resulting epigenome facilitates the organisation of RNA polymerase II into transcription factories and regulatory hubs that help establish and maintain gene expression patterns during development [ 1 ]. Histones, in association with DNA form nucleosomes, the fundamental units of chromatin. Initially described as barriers to transcription, decades of chromatin research have since revealed that nucleosomes play far more nuanced roles, acting through post-translational modifications that can either promote or repress transcription [ 2 , 3 ]. One of these modifications occurs on Histone 3 at Lysine 4 (H3K4me) and involves the covalent attachment of up to three methyl groups to form mono-, di-, or tri-methylated forms (H3K4me1, me2, and me3). These three modifications have distinct patterns of deposition and are broadly associated with transcriptionally active genes [ 4 ]. H3K4me3 is the most notable of these modifications as it is strongly correlated with active Transcription Start Sites (TSS) [ 5 , 6 ]. H3K4me3 can regulate initiation and elongation during proximal-promoter pause-release of RNA-pol II [ 4 , 7 – 9 ]. In addition to these roles, studies have shown that H3K4me2/me3 can generate bivalent domains when coupled with H3K27me2/me3. These bivalent domains regulate expression of developmental genes, which are initially repressed but poised to later resolve their transcriptional state [ 10 ]. In addition, H3K4me2 can also mediate non-coding RNA-mediated repression of Hox genes [ 11 ], whilst both H3K4me2 and H3K4me3 can suppress cryptic transcription [ 12 – 15 ]. Furthermore, enrichment in H3K4me1 together with H3K27 acetylation define transcriptionally active enhancers [ 16 , 17 ]. Collectively, these studies suggest that alterations in H3K4 methylation may compromise transcriptional states by perturbing both activating and repressive mechanisms. H3K4 methylation is catalysed by the evolutionarily conserved SET/COMPASS and MLL (Mixed Lineage Leukaemia) complexes [ 18 – 20 ] referred to hereafter collectively as the SET/MLL complex. These complexes consist of SET domain-containing methyltransferases (KMT2 enzymes) and a core scaffolding complex that together transfer methyl groups from the universal donor S-adenosylmethionine to H3K4, generating H3K4me1/me2/me3 (Fig. 1 A;[ 21 ]). Notably, the number of KMT2 enzymes increases with species complexity: one in S. cerevisiae ; two in C. elegans ; three in Drosophila ; and six in mammals [ 22 , 23 ]. These enzymes form distinct SET/MLL sub-complexes that share core components but also include specific co-factors. The main core subunits are WDR5, RBBP5, ASH2L, and DPY30, which associate with co-factors such as CFP1 or Menin to form SET or MLL complexes, respectively [ 24 ]. Interestingly, WDR5 is also found in other chromatin-modifying complexes containing HAT or HDAC activities [ 25 – 32 ], challenging the attribution of WDR5-dependent transcriptional changes solely to its role in H3K4 methylation. In C. elegans , the SET/MLL complex is comprised of two KMT2 enzymes: SET-2, a SET orthologue [ 33 ] and SET-16, an MLL-like enzyme [ 34 ]. The scaffolding subunits WDR-5, ASH-2, and RBBP-5 are highly conserved across species [ 33 – 36 ]. Independent loss of these scaffolding components alters H3K4 methylation and leads to phenotypes including altered lifespan [ 37 – 40 ], erroneous hindgut-to-neuron transdifferentiation [ 41 ], increased RAS signalling in vulval cells [ 34 ], axon guidance defects [ 42 ] and disrupted germ cell pluripotency [ 43 , 44 ]. SET-16-dependent H3K4me3 also contributes to innate immunity [ 45 ]. Despite the clear roles of these components in H3K4 methylation, a comparative, quantitative analysis of their individual contributions has been lacking. Herein, we determined the contribution of WDR-5 and RBBP-5 towards all three H3K4 methylation states using spike-in ChIP-seq on C. elegans embryos (Fig. 1 B). We found that WDR-5 primarily prevents the deposition of tri-methyl groups at H3K4. In contrast, the absence of RBBP-5 abrogates all three states of H3K4 methylation. RNA-seq analysis show that rbbp-5(-) mutant embryos displayed fewer transcriptomic changes than wdr-5(-) embryos (721 versus 3377 Differentially Expressed Genes, respectively). Furthermore, the transcriptome of the rbbp-5(-); wdr-5(-) double mutant, which lacks H3K4 methylation, closely resembled the wdr-5(-) single mutant. This indicates that gene expression changes in the wdr-5(-) mutant occur largely independently of H3K4 methylation. Together, our findings reveal that WDR-5 is required for H3K4me3 deposition and that it acts in parallel to H3K4 methylation to regulate gene expression. Materials and Methods Strains and general maintenance C. elegans strains were maintained at 20°C and as described in Brenner et al. [ 46 ]. Strains used in this study are: N2 (wild type), wdr-5.1(ok1417) III (RB1304), rbbp-5(tm3463) II , and the double rbbp-5(tm3463) II; wdr-5.1(ok1417) III (OL76). Embryonic preparation on large solid media plates for spike-in ChIP-seq Synchronised population of embryos were prepared on solid NGM media from bleached young adult hermaphrodites. These adults were harvested from two rounds of amplifications; each performed on 20 Corning tissue culture dishes (245 x 245 mm) that were seeded with synchronised L1 (larval stage 1) obtained from bleaching large numbers of gravid adults. To obtain these large populations of worms, dishes were seeded with 0.5 ml of 20x OP50 stock and left to dry for at least two days before use. 20 dishes per strain were seeded with synchronised L1s: ~1,000 L1s for N2 (wild type), ~ 2,000 L1s for wdr-5(-) , and ~ 3,000 L1s for rbbp-5(-) . When the next generation reached L4 stage, all worms were harvested and transferred onto 20 new dishes to prevent starvation and mature adults were bleached to generate large populations of synchronised L1s, which were all re-seeded onto 20 dishes. These L1s were grown to obtain young adults, a stage reached after 54h for N2 (wild type), and 64h for wdr-5(-) and rbbp-5(-) . Following bleaching of these adults, embryos were collected on sucrose gradients and re-suspended in 47 ml of M9 buffer and 2.8 ml of 37% formaldehyde solution (~ 2% final). Embryos were placed on a shaker (50 rpm) at room temperature for 30 minutes, then spun down and the pellets quenched by adding 50 ml of 100 mM Tris buffer (pH 7.5) to stop the fixation process. Fixed embryos were spun down and washed twice with 50 ml M9, then 10 ml FA buffer (50 mM HEPES/KOH pH 7.5, 1 mM EDTA pH 8, 1% Triton x-100, 0.1% sodium deoxycholate, 150 mM NaCl) containing protease inhibitor cocktail was added to the pellet. Between 200 µl and 500 µl of packed embryos can be obtained from this method. Next, an aliquot of 5 µl of embryos for each genotype was taken out, treated with methanol, and stained with DAPI for scoring on standard 2% agarose pad with a coverslip (store at -20°C). The embryo preparations used for N2 (wild type), wdr-5(-) , and rbbp-5(-) were comparable: 20–40% at < 28-cell stages; 20–27% between 28-cell and 100-cell stages; 32–52% at pre-coma stage; and 0–4% at coma stage or beyond. Then, samples were prepared as previously described [ 47 ]. Briefly, embryo pellets were re-suspended in a total of 1.5 ml FA buffer (50 mM HEPES/KOH pH 7.5, 1 mM EDTA pH 8, 1% Triton x-100, 0.1% sodium deoxycholate, 150 mM NaCl) with protease inhibitor cocktail. Embryos were dounced 40 times on ice using a pastel B homogeniser and aliquoted in 250 µl into six 1.5 ml microtubes. Sonication was performed using the Bioruptor UCD-200 (30 sec ON, 30 sec OFF) with ultrasonic wave output at HIGH for three 5 min cycles. Between cycles, the samples were cooled in a dry ice/ethanol bath for 5 sec. A small aliquot was kept to verify the DNA size on a 1.5% agarose gel showing enrichment between 400–600 bp. In the meantime, the samples were snap frozen and kept at -80°C. The frozen embryonic samples were then shipped to ActiveMotif on dry ice to perform the spike-in ChIP-seq procedure [ 48 ]. Briefly, about 5% of D. melanogaster was added to C. elegans embryo chromatin. 0.4 µg of the anti-H2Av antibody (AM39715) was used to immunoprecipitate D. melanogaster chromatin from each reaction, which is then used as a reference for normalisation. The antibodies are from ActiveMotif and are: anti-H3K4me1 (AM39297), anti-H3K4me2 (AM39141), and anti-H3K4me3 (AM39159). Spike-in ChIP-seq libraries and data processing Illumina sequencing libraries were prepared from the ChIP and input DNAs by the standard consecutive enzymatic steps of end-polishing, dA-addition, and adaptor ligation. After a final PCR amplification step, the resulting DNA libraries were quantified and sequenced on Illumina’s NextSeq 500 (75 nt reads, single end). All genomic analyses were performed using the Caenorhabditis elegans genome build WS220 (ce10). ChIP-seq reads were aligned to the ce10 genome using Bowtie2 v2.3.4 and processed with Samtools v1.9 and Picard. Duplicate reads were removed using MarkDuplicates, and mitochondrial reads were filtered out. To account for GC content bias, we applied computeGCBias and correctGCBias from DeepTools (v3.5.6) [ 49 ]. Normalisation by downsampling was carried out on the GC-corrected BAM files using Picard and spike-in normalisation factors applied. Final normalised coverage tracks (BigWigs) were generated from the downsampled, GC-corrected BAM files using bamCoverage with CPM normalisation and a bin size of 10 bp. These tracks were used in all downstream DeepTools analyses, including heatmaps, metagene plots, and principal component analysis. Peak locations for overall genomic enrichment were determined using the MACS2 algorithm (v2.2.9.1) with an effective genome size of 9.3×10⁷ and a q-value threshold of 0.05 [ 50 ]. For H3K4me2 and H3K4me3, broad peaks were called using default model-based parameters with a broad cutoff of 0.1. For H3K4me1, due to poor model estimation, peaks were called using ‘nomodel’ mode and a fixed fragment extension size of 147 bp. All peak calls were performed on GC-bias-corrected BAM files using matched input controls. The N2 wild type data were benchmarked against modEncode publicly available early embryonic ChIP-seq dataset (H3K4me1 repl 1: GSM1217259 repl 2: GSM1217260 input: GSM1217261; H3K4me2 repl 1: GSM1206344 repl 2: GSM1206345 input: GSM1206346; H3K4me3 repl 1: GSM1206368 repl 2: GSM1206369 input: GSM1206370) [ 51 ]. To compare H3K4me1, H3K4me2, and H3K4me3 levels between wild type and mutants, Transcription Start Sites (TSS) generated by Chen et al. [ 52 ] and active enhancers mapped by Janes et al. [ 53 ] were used. Normalised bigWig files containing ChIP-seq signal coverage were analysed using Deeptools [ 49 ]. The bigWig files corresponding to wild-type (WT), wdr-5(-) , and rbbp-5(-) conditions were GC bias-corrected and normalised. BED files defining TSS and enhancer regions were uploaded for further processing. Embryonic preparations for RNA-seq Synchronised populations of adult worms for N2, rbbp-5(-) , wdr-5(-) and rbbp-5(-); wdr-5(-) were grown on 10 cm plates. Young adults were bleached and the embryos scored for developmental stages using DIC microscopy. The populations were consistently between ~ 25–30% at 28–100 cell stage, ~ 45–55% at pre-coma stage, and ~ 5–15% at late embryogenesis stages, roughly matching the spike-in ChIP-seq samples. Three biological replicates were prepared per genotype. Total RNA was extracted using TRIzol (Invitrogen) and stored at -80°C until sent for analysis to the Genomic core facility at the Faculty of Biology, Medicine and Health (University of Manchester). RNA-seq libraries and analysis RNA-seq libraries were generated using the TruSeq Stranded mRNA Sample Preparation Kit (Illumina), followed by 101 × 101 bp paired-end sequencing on the Illumina HiSeq platform. Across 12 libraries, an average of ~ 208 million paired-end reads per sample were obtained (range: 100–422 million), with an average alignment rate of 94% to the C. elegans reference genome (ce10). Mate 1 and mate 2 reads were balanced across all samples, indicating high-quality libraries. FastQC and Trimmomatic [ 54 ] were used for quality control and adapter trimming. Reads were aligned using TopHat 2.1.0 [ 55 ], and gene-level quantification was performed using HTSeq [ 56 ] with the c_elegans WS220.annotations.gtf annotation file. Differentially expressed genes (DEGs) were identified using DESeq2 [ 57 ], applying thresholds of fold change > 2 and adjusted p-value < 0.05 with a cut-off for read counts set at 50 as detected in wild type and/or mutant samples. Calculation of Net Transcriptome Change Percent To assess the global directional impact of transcriptomic changes in mutants relative to wild type, we calculated the Net Transcriptome Change Percent by integrating the direction of expression change (log₂ fold change) with the level of gene expression (baseMean) for differentially expressed genes (DEGs). Only DEGs passing thresholds for both adjusted p-value and fold change were included in this analysis. For each mis-regulated gene, the baseMean (mean normalised expression across all samples) was multiplied by its log₂-transformed fold change (log₂FC). The contributions of all mis-regulated genes were summed to produce the Net Directional Change. The baseMean values for all DEGs were summed to calculate the Total BaseMean, representing the total transcript abundance for all mis-regulated genes irrespective of regulation direction. The Net Transcriptome Change Percent was calculated by expressing the Net Directional Change as a proportion of the Total BaseMean and multiplied by 100. This metric provides a global estimate of the directional bias in transcriptomic change, expressed as a percentage of the total mis-regulated gene expression. Negative percentages indicate net down-regulation; positive percentages indicate net up-regulation. Statistical test on the Violin plots We tested whether genes classified as up-regulated, down-, or mis-regulated in a mutant background tend to have different expression levels in wild type compared to unregulated genes, using the baseMeanA metric (representing average wild-type expression). We performed a Mann-Whitney U test, also called a Pairwise Wilcoxon rank-sum tests, applied to log2-transformed baseMeanA values to assess distributional shifts across categories. ChIP-seq and RNA-seq data access The ChIP-seq data have been deposited in the GEO repository under ID code GSE94639 and RNA-seq data have been deposited in the ArrayExpress repository under ID code E-MTAB-15080. Results Benchmarking H3K4 mono- and multi-methylation spike-in ChIP-seq data To assess the in vivo contributions of RBBP-5 and WDR-5 to H3K4 methylation, we performed spike-in ChIP-seq on C. elegans embryos for H3K4me1, H3K4me2, and H3K4me3. This approach enables accurate comparison across genotypes, especially important given the expected global reduction in H3K4 methylation in rbbp-5(-) and wdr-5(-) mutants. Spike-in normalisation is critical for such cross-genotype comparisons in ChIP-seq [ 58 ]. In our study, we used Drosophila chromatin and an antibody against the Drosophila -specific histone variant H2Av to normalise for technical variability during the ChIP process [ 48 ]. Normalisation analysis confirmed its necessity, particularly in the rbbp-5(-) background for all three marks (H3K4me3/me2/me1; Suppl. Figure 1). In the wdr-5(-) mutant, the normalisation also produced a reduction in the number of usable tags, but to a lesser extent than in the rbbp-5(-) mutant. By contrast, the wild type samples were either unaffected (H3K4me3/me2) or only marginally affected (H3K4me1) by normalisation (Suppl. Figure 1). To benchmark data quality, we compared our spike-in ChIP-seq datasets with publicly available modENCODE H3K4me1/2/3 data [ 47 , 51 ]. Principal Component Analysis (PCA) demonstrated clustering of our samples alongside modENCODE replicates according to H3K4 methylation state (Suppl. Figure 2A), confirming reproducibility. Pearson correlation analysis further validated high concordance between our data and the modENCODE datasets (Suppl. Figure 2B). Finally, we assessed the genomic distribution of H3K4 methylation at transcription start sites (TSS) of protein-coding genes and at active enhancers [ 52 , 53 ]. As expected, H3K4me3 was enriched at TSS (Fig. 2 A), whilst H3K4me1 showed characteristic enhancer enrichment (Fig. 2 B), consistent with published data [ 47 , 53 ]. Together, these analyses confirm that our spike-in ChIP-seq data are robust, well-normalised, and comparable to established datasets. RBBP-5 is required for bulk H3K4 methylation, whilst WDR-5 is critical for H3K4me3 To establish the contribution to H3K4 methylation from these scaffolding components, we compared the deposition of H3K4 mono- and multi-methylation between wild-type (N2) and the wdr-5(-) and rbbp-5(-) mutants. We first analysed H3K4me3 enrichment. In the absence of RBBP-5, H3K4me3 was almost completely lost at both TSS and enhancers (Fig. 3 A and B). In wdr-5(-) embryos, H3K4me3 levels were also markedly reduced at TSS and enhancers, although the depletion was less severe than in the rbbp-5(-) mutant (Fig. 3 A and B). Global H3K4me3 levels mirrored these findings, with the most pronounced reduction observed in the absence of RBBP-5 (Fig. 3 C). We also constructed a schematic model to illustrate the relative contributions of RBBP-5 and WDR-5 (Fig. 3 D). We next examined H3K4me2 deposition. As with H3K4me3, the absence of RBBP-5 resulted in an almost complete loss of H3K4me2 enrichment at both TSS and enhancers (Fig. 4 A and B). In contrast, the effects of WDR-5 loss on H3K4me2 were context-dependent: H3K4me2 levels were reduced at TSS, but increased at enhancers (Fig. 4 A and B). These opposing changes appeared to balance each other, resulting in no significant difference in the global H3K4me2 levels (Fig. 4 C). We incorporated these context-specific effects into our schematic model to reflect the nuanced contribution of WDR-5 to H3K4me2 deposition (Fig. 4 D). Finally, we analysed H3K4me1 levels. RBBP-5 was essential for H3K4me1 deposition at both TSS and enhancers (Fig. 5 A and B), a requirement that also held true at the global level (Fig. 5 C). In contrast, the absence of WDR-5 led to an increase in H3K4me1 at TSS, enhancers, and globally (Fig. 5 A–C). This accumulation may result from impaired progression to higher methylation states, leading to the build-up of H3K4me1. These data were integrated into our schematic to illustrate the distinct roles of RBBP-5 and WDR-5 in regulating H3K4me1 (Fig. 5 D). Overall, these results show that RBBP-5 is essential for all H3K4 methylation states, whereas WDR-5 is primarily required for H3K4me3. These findings highlight the distinct roles of these scaffolding components in shaping the H3K4 methylation landscape. Chromosome X is differentially impacted by the absence of WDR-5 relative to autosomes To address whether the absence of WDR-5 affects each chromosome similarly, we analysed H3K4 methylation enrichment at TSS for each chromosome individually. In wild type, the chromosomes with highest levels of H3K4me3 levels were chromosomes I and III, whilst chromosomes II and IV displayed intermediate levels, and chromosomes X and V showed the lowest levels (Fig. 6 A). We examined how this chromosomal hierarchy of H3K4me3 levels was affected in the wdr-5(-) mutant. As expected, we found a striking reduction, but chromosome X was not as profoundly affected (Fig. 6 B). We next analysed H3K4me2 levels and found that chromosomes clustered similarly to the H3K4me3 analysis with high and intermediate levels still being represented by chromosome I and III and chromosome II and IV, respectively. However, relative H3K4me2 levels increased on chromosome X (Fig. 6 C). Interestingly, in the absence of WDR-5, autosomes exhibited a reduction in H3K4me2 enrichment, but the chromosome X displayed a robust increase (Fig. 6 D). We then analysed the levels of H3K4me1, and found that in wild type, chromosome X was among the chromosomes with the highest and most characteristic H3K4me1 enrichment (Fig. 6 E). As expected, in the wdr-5(-) deletion, all chromosomes displayed an increase in the levels of H3K4me1, but the chromosome X was the most affected (Fig. 6 F). Together these findings reveal that while WDR-5 is broadly required for H3K4 multi-methylation across the autosomes, chromosome X appears to be subject to a WDR-5-independent regulatory mechanism that sustains or even enhances H3K4 multi-methylation in its absence (Fig. 6 G). WDR-5 has a greater impact on the transcriptome than RBBP-5 Given the distinct effects of WDR-5 and RBBP-5 on H3K4 methylation, we next asked how these differences would be reflected at the transcriptome level. To address this, we performed RNA-seq on staged embryos and identified differentially expressed genes (DEG) relative to wild type. In wdr-5(-) embryos, we identified 3377 DEG, comprising 1108 down-regulated genes and 2269 up-regulated genes (Fig. 7 A, Table S1 ). In contrast, the rbbp-5(-) mutant exhibited only 721 DEGs, with 60 down-regulated and 661 up-regulated (Fig. 7 B, Table S1 ). The predominance of up-regulated genes was to an extent unexpected, given the association of H3K4 methylation with active transcription, though previous studies have also noted this prevalence. Our findings are therefore consistent with prior transcriptomic analyses comparing wdr-5(-) and set-2(-) mutants in dissected C. elegans gonads. The authors similarly reported a bias towards up-regulation [ 44 ]. However, another study using set-2 mutants in early embryos reported a more balanced distribution of down- and up-regulated genes [ 32 ]. Upon re-analysing this early embryonic dataset [ 32 ] with both a two-fold change cutoff and padj < 0.05, we found an enrichment for up-regulated genes (587 up versus 203 down; Table S2 ), which is in line with our findings. To assess the performance of DESeq2 normalisation, we generated MA plots for each comparison (Fig. 7 C, D). Data points were centred around log2 fold change = 0 at low expression levels, confirming successful normalisation. The data are also consistent with the effects observed on the wdr-5(-) and rbbp-5(-) respective transcriptomes, whereby more genes are up-regulated than down-regulated in both mutants. We next asked whether down-regulated genes in the mutants tend to be highly expressed in wild type, given the known association between highly expressed genes and H3K4 methylation. To assess this point, we separated the data into down-, up-, and un-regulated genes and plotted their associated levels of expression in wild type (baseMean wild type) for each corresponding mutant (Fig. 7 E and F). Indeed, down-regulated genes in each mutant exhibited significantly higher expression in wild type than up-regulated genes and un-regulated genes (pval < 0.01), suggesting that these down-regulated genes are more likely to represent direct WDR-5 or RBBP-5 targets (Fig. 7 E, F). Finally, to assess the global impact of WDR-5 and RBBP-5 loss on their respective transcriptomes, we quantified the net directional change in expression across all DEG. This metric integrates both the direction (log2 fold change) and magnitude (baseMean) of expression changes to summarise transcriptomic shifts. In wdr-5(-) embryos, we observed a net change of -28%, indicating an overall decrease in gene expression among mis-regulated genes (Table S3 ). In contrast, rbbp-5(-) embryos showed a milder net change of -9% (Table S3 ). Thus, while both mutants exhibit more up- than down-regulated genes, the overall net effect is a reduction in number of transcripts. This effect is more pronounced in wdr-5(-) , consistent with its broader transcriptomic perturbation (Fig. 7 A and B). WDR-5 exhibits H3K4 methylation-independent functions impacting on gene expression We next asked the question whether the large number of DEG in wdr-5(-) could be attributed to the persistence of H3K4me1, H3K4me2 or residual H3K4me3. To test this, we generated an rbbp-5(-); wdr-5(-) double mutant, in which H3K4 methylation is unlikely because of the absence of RBBP-5. We made two predictions as to how the rbbp-5(-); wdr-5(-) double mutant would affect transcription (Fig. 8 A-C). One is that the transcriptomic profile of the double mutant will resemble that of rbbp-5(-) alone (~ 700 DEG) because the perturbations in the wdr-5(-) transcriptome are explained by persistent H3K4me1, H3K4me2 or residual H3K4me3 (Fig. 8 C; left panel). The second possibility is that the transcriptomic profile of the double mutant will mirror the wdr-5(-) transcriptome (~ 3000 DEG) because the absence of RBBP-5 does not interfere with WDR-5 parallel activity (Fig. 8 C; right panel). It turns out that the rbbp-5(-); wdr-5(-) double mutant exhibited 3682 DEG (Fig. 8 D), a number comparable to the wdr-5(-) single mutant (3377 DEGs; Fig. 7 A). Clustering analysis (Fig. 8 E) and Venn diagrams (Suppl. Figure 3) confirmed substantial overlap between the DEG of the double and wdr-5(-) mutants. Moreover, a large proportion of the DEG identified in rbbp-5(-) were also found in wdr-5(-) and in the double mutant, consistent with both proteins acting within the SET/MLL complex (Suppl. Figure 3). However, the broader transcriptional changes observed in the absence of WDR-5 (even when H3K4 methylation is abolished) strongly suggest that WDR-5 has additional functions beyond promoting H3K4 methylation. We next compared Gene Ontology categories between the three datasets using WormCat 2.0 [ 59 ] and found that many of the categories are shared between the single wdr-5(-) and rbbp-5(-) mutants and the double rbbp-5(-); wdr-5(-) mutant, indicating that those functions such as neuronal and stress response are likely regulated, at least in part, by H3K4 methylation (Fig. 9 ). Other WormCat categories (transcription factors, cytoskeleton, and cilia) are shared between the single wdr-5(-) mutant and the double rbbp-5(-); wdr-5(-) mutant and these are likely regulated by WDR-5 parallel activity. Taken together, these data show that the transcriptomes of the single wdr-5(-) and the double rbbp-5(-); wdr-5(-) mutants share a high degree of similarity, indicating that WDR-5 can affect gene expression independently of H3K4 methylation during C. elegans embryogenesis. Discussion Our study shows that WDR-5 and RBBP-5 have distinctive roles in the deposition of methyl marks at H3K4. WDR-5 facilitates H3K4 tri-methylation, whilst RBBP-5 is necessary for mono- and multi-methylation. These functions align with cryo-EM structural studies showing that RBBP5 plays a central role in nucleating the MLL1 core complex on the nucleosome, and engaging both its DNA and histone surfaces to orient the complex [ 21 , 60 – 62 ]. Our data are also largely consistent with other studies performed on C. elegans embryos [ 35 , 36 , 63 ]. We also show that WDR-5 has intricate and more subtle functions; its absence reduces H3K4 methylation more prominently on autosomes than on the sex chromosome and the effects on deposition of H3K4me2 can be either positive or negative depending on the genomic features involved. Crucially, we were able to functionally demonstrate that WDR-5 exhibits H3K4 methylation-independent activity by analysing the transcriptome of a double mutant between rbbp-5(-) and wdr-5(-) and comparing it with the single mutants. Our study shows that WDR-5 has profound impacts on gene expression that are independent of its role in H3K4 methylation. WDR-5 is found physically associated with additional chromatin complexes. These ‘moonlighting’ activities are likely explaining our results whereby the alterations in the transcriptome of the wdr-5(-) mutant are more profound than in the rbbp-5(-) transcriptome. This conclusion is based on our results from the double rbbp-5(-); wdr-5(-) mutant showing that most of these wdr-5(-) alterations in gene expression are independent of H3K4 methylation, since H3K4 methylation is abrogated without RBBP-5. Thus, our work supports the proposal by Guarnaccia et al. that WDR-5 acts as a multi-functional hub in the nucleus [ 25 ]. WDR5 was first characterised in mammals as a core component of the H3K4 methylation complex [ 64 ]. However, it was later found in other complexes notably the NSL (Non-Specific Lethal) and ATAC (Ada Two A Containing) histone acetyltransferase complexes [ 28 , 65 ]. WDR5 can also be found in histone deacetylases complexes such as RPD3 HDAC in yeast (or mSin3a-HDAC1 in mammals) and the NuRD complex [ 31 ]. ING2, a component of the sSin3a-HDAC1, interacts via its PHD domain with H3K4me3 to stimulate deacetylation and repress transcription [ 66 ]. In yeast, it was found that H3K4me2/me3 can recruit RPD3 HDAC to repress cryptic transcription [ 14 ]. In C. elegans , WDR-5 is found within the Sin3S HDAC repressive complex [ 32 ], which is similar to RPD3 HDAC in yeast and sSin3a-HDAC1 in mammals. Interestingly, work in other species support an H3K4 methylation-independent role for WDR5. WDR5 point mutations defective in H3K4 methylation could still rescue specific phenotypes such as mouse embryonic stem cells self-renewal defects and de-repression of germ cell specific genes [ 67 ] as well as left-right patterning of the heart in Xenopus [ 68 ], indicating that H3K4 methylation-independent activity is conserved in vertebrates. Thus, WDR-5 appears to act as a multi-functional hub regulating both activation and context-dependent repression of transcription via H3K4 methylation as well as histone acetylation and deacetylation. This promiscuous activity most likely explains the effects on the wdr-5(-) transcriptome reported herein. However, whether and how any of these activities are privileged over others remains to be elucidated. In contrast to WDR-5, RBBP-5 is critical and specific to the deposition of H3K4 methyl groups. Concordant with our work, a study investigating crosstalk between the NSL and SET/MLL complexes in Drosophila has shown that depletion of RBBP5 affects H3K4me2 deposition but not H4K16 acetylation, indicating that RBBP5 is not directly affecting histone acetylation, whereas WDR5 inactivation can affect both H3K4 methylation and H4K16 acetylation [ 29 ]. In addition, a C. elegans study investigating masculinisation of the germline found that this phenotype arises in the absence of WDR-5 but not in the absence of RBBP-5, indicating that WDR-5 has H3K4 methylation-independent activity but not RBBP-5 [ 69 ]. It is also interesting to note that loss-of-function mutations in RBBP-5 in humans have recently been identified and associated with neurodevelopmental disorder, short stature and microcephaly [ 70 ], highlighting the importance of H3K4 methylation for neuronal function. Our analysis has also revealed a chromosomal hierarchy in H3K4me3 enrichment at transcription start sites, which closely mirrors the pattern of phenotypic enrichment observed through systematic RNAi screening [ 71 ]. Specifically, chromosomes I and III exhibit the highest levels of H3K4me3, followed by chromosomes II and IV, and with chromosomes V and X showing the lowest enrichment. This pattern is consistent with previous findings showing that chromosomes I and III are relatively enriched for active chromatin marks, including H3K4 methylation, whereas chromosomes V and X are comparatively depleted [ 47 ]. One possible explanation linking H3K4me3 enrichment to RNAi phenotypic outcomes is that genes which are robustly transcribed (and therefore more heavily marked by H3K4me3) are more likely to yield observable phenotypes when knocked down by RNAi. Although the mechanisms coordinating transcriptional regulation at the chromosome-wide level remain poorly understood, it is plausible that differential H3K4me3 enrichment reflects the partitioning of chromosomes into distinct chromatin environments during early embryogenesis. Higher levels of H3K4me3 on chromosomes I and III may indicate a more open, transcriptionally permissive architecture, possibly maintained through large-scale domain organisation or preferential spatial positioning within the nucleus. Conversely, the lower H3K4me3 levels on chromosomes V and X could reflect sequestration into less active chromatin territories. Notably, data from a recent C. elegans study investigating partitioning of chromatin states in the germlines has also revealed that transcriptionally active domains (marked by high H3K4me3 and H3K36me3) follow a similar chromosomal hierarchy [ 72 ]. These chromosome-wide biases in chromatin accessibility and transcriptional competence may underlie the observed correspondence between H3K4me3 and RNAi phenotype enrichment. Our chromosome-level analysis also shows that H3K4me1 enrichment and distribution at TSS on chromosome X are distinct from those on autosomes. It is therefore tempting to speculate that H3K4me1 could play a role on chromosome X to dampen transcription. Alternatively, as shown during the early stages of X chromosome inactivation in mammals [ 73 ], elevated H3K4me1 levels may reflect reduced transcription and the incomplete conversion into H3K4me2 and H3K4me3. There is also the possibility that the SET/MLL complex could play a role in regulating the dosage compensation (DC) complex. It has been shown that DPY-30, an additional scaffolding component of the SET/MLL complex, is also present in the DC complex [ 74 ]. The authors show that DPY-30 and ASH-2 are found at a subset of sites known to be critical for dosage compensation. Since ASH-2 knockdown does not affect the recruitment and function of the DC complex, it seems that the SET/MLL complex would act downstream or in parallel. It is plausible that the co-localisation of the DC and SET/MLL complexes at the same DC binding sites prevents enrichment of H3K4me3 and thereby increases the levels of H3K4me1, which would be consistent with our findings. Conclusion Together, our findings establish that WDR-5 and RBBP-5 exert distinct functions in chromatin regulation, with WDR-5 having a broader influence on gene expression through mechanisms most likely beyond H3K4 methylation. This highlights WDR-5 as a versatile regulatory scaffold in chromatin biology. Future work will be needed to determine how WDR-5’s roles across different chromatin-modifying complexes are coordinated, and whether specific chromatin contexts favour particular functions over others. Defining the precise interactome of WDR-5 in vivo will help clarify these mechanisms and further understanding of its roles in development and disease. Declarations Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Availability of data and materials: The ChIP-seq data have been deposited in the GEO repository under ID code GSE94639 and RNA-seq data have been deposited in the ArrayExpress repository under ID code E-MTAB-15080. Competing interests: The authors declare that they have no competing interests. Funding: This work was in part supported by the Biotechnology and Biological Sciences Research Council (BB/J014834/1) and by the Wellcome Trust [097820/Z/11/Z]. Some strains were provided by the CGC (Caenorhabditis Genetics Center). The CGC is funded by NIH Office of Research Infrastructure Programs [P40 OD010440]. Authors' contributions: The conception and experimental design, the analysis and interpretation of the data, and writing of the manuscript was performed by GP. NBS and KF have performed laboratory work necessary for acquisition of the data. Acknowledgements: We thank A. Hayes, his team, L. Zeef and P. Wang of the Bioinformatics and Genomic Technologies Core Facilities at the University of Manchester for providing support regarding RNA-seq experiments. Dr. Siyao Wang, former PhD student from the Poulin lab, for contributing towards the generation of the double rbbp-5(-); wdr-5(-) mutant. Our colleagues Prof. Andy Sharrocks and Dr. Alan Whitmarsh for providing valuable advice on the manuscript. References Palacio M, Taatjes DJ: Merging Established Mechanisms with New Insights: Condensates, Hubs, and the Regulation of RNA Polymerase II Transcription. J Mol Biol 2022, 434: 167216. Bannister AJ, Kouzarides T: Regulation of chromatin by histone modifications. Cell Res 2011, 21: 381-395. Kouzarides T: Chromatin modifications and their function. Cell 2007, 128: 693-705. Wang H, Helin K: Roles of H3K4 methylation in biology and disease. Trends Cell Biol 2024. Barski A, Cuddapah S, Cui K, Roh TY, Schones DE, Wang Z, Wei G, Chepelev I, Zhao K: High-resolution profiling of histone methylations in the human genome. Cell 2007, 129: 823-837. Guenther MG, Levine SS, Boyer LA, Jaenisch R, Young RA: A chromatin landmark and transcription initiation at most promoters in human cells. Cell 2007, 130: 77-88. Hu S, Song A, Peng L, Tang N, Qiao Z, Wang Z, Lan F, Chen FX: H3K4me2/3 modulate the stability of RNA polymerase II pausing. Cell Res 2023, 33: 403-406. Santos-Rosa H, Schneider R, Bannister AJ, Sherriff J, Bernstein BE, Emre NC, Schreiber SL, Mellor J, Kouzarides T: Active genes are tri-methylated at K4 of histone H3. Nature 2002, 419: 407-411. Wang H, Fan Z, Shliaha PV, Miele M, Hendrickson RC, Jiang X, Helin K: H3K4me3 regulates RNA polymerase II promoter-proximal pause-release. Nature 2023, 615: 339-348. Bernstein BE, Mikkelsen TS, Xie X, Kamal M, Huebert DJ, Cuff J, Fry B, Meissner A, Wernig M, Plath K, et al: A bivalent chromatin structure marks key developmental genes in embryonic stem cells. Cell 2006, 125: 315-326. Rinn JL, Kertesz M, Wang JK, Squazzo SL, Xu X, Brugmann SA, Goodnough LH, Helms JA, Farnham PJ, Segal E, Chang HY: Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs. Cell 2007, 129: 1311-1323. Briggs SD, Bryk M, Strahl BD, Cheung WL, Davie JK, Dent SY, Winston F, Allis CD: Histone H3 lysine 4 methylation is mediated by Set1 and required for cell growth and rDNA silencing in Saccharomyces cerevisiae. Genes Dev 2001, 15: 3286-3295. Kim T, Buratowski S: Dimethylation of H3K4 by Set1 recruits the Set3 histone deacetylase complex to 5' transcribed regions. Cell 2009, 137: 259-272. Pinskaya M, Gourvennec S, Morillon A: H3 lysine 4 di- and tri-methylation deposited by cryptic transcription attenuates promoter activation. EMBO J 2009, 28: 1697-1707. Ryu HY: Histone Modification Pathways Suppressing Cryptic Transcription. Epigenomes 2024, 8 . Creyghton MP, Cheng AW, Welstead GG, Kooistra T, Carey BW, Steine EJ, Hanna J, Lodato MA, Frampton GM, Sharp PA, et al: Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proc Natl Acad Sci U S A 2010, 107: 21931-21936. Heintzman ND, Hon GC, Hawkins RD, Kheradpour P, Stark A, Harp LF, Ye Z, Lee LK, Stuart RK, Ching CW, et al: Histone modifications at human enhancers reflect global cell-type-specific gene expression. Nature 2009, 459: 108-112. Miller T, Krogan NJ, Dover J, Erdjument-Bromage H, Tempst P, Johnston M, Greenblatt JF, Shilatifard A: COMPASS: a complex of proteins associated with a trithorax-related SET domain protein. Proc Natl Acad Sci U S A 2001, 98: 12902-12907. Nagy PL, Griesenbeck J, Kornberg RD, Cleary ML: A trithorax-group complex purified from Saccharomyces cerevisiae is required for methylation of histone H3. Proc Natl Acad Sci U S A 2002, 99: 90-94. Roguev A, Schaft D, Shevchenko A, Pijnappel WW, Wilm M, Aasland R, Stewart AF: The Saccharomyces cerevisiae Set1 complex includes an Ash2 homologue and methylates histone 3 lysine 4. EMBO J 2001, 20: 7137-7148. Xue H, Yao T, Cao M, Zhu G, Li Y, Yuan G, Chen Y, Lei M, Huang J: Structural basis of nucleosome recognition and modification by MLL methyltransferases. Nature 2019, 573: 445-449. Shilatifard A: The COMPASS family of histone H3K4 methylases: mechanisms of regulation in development and disease pathogenesis. Annu Rev Biochem 2012, 81: 65-95. Wenzel D, Palladino F, Jedrusik-Bode M: Epigenetics in C. elegans: facts and challenges. Genesis 2011, 49: 647-661. Sze CC, Shilatifard A: MLL3/MLL4/COMPASS Family on Epigenetic Regulation of Enhancer Function and Cancer. Cold Spring Harb Perspect Med 2016, 6 . Guarnaccia AD, Tansey WP: Moonlighting with WDR5: A Cellular Multitasker. J Clin Med 2018, 7 . Dou Y, Milne TA, Tackett AJ, Smith ER, Fukuda A, Wysocka J, Allis CD, Chait BT, Hess JL, Roeder RG: Physical association and coordinate function of the H3 K4 methyltransferase MLL1 and the H4 K16 acetyltransferase MOF. Cell 2005, 121: 873-885. Mendjan S, Taipale M, Kind J, Holz H, Gebhardt P, Schelder M, Vermeulen M, Buscaino A, Duncan K, Mueller J, et al: Nuclear pore components are involved in the transcriptional regulation of dosage compensation in Drosophila. Mol Cell 2006, 21: 811-823. Dias J, Van Nguyen N, Georgiev P, Gaub A, Brettschneider J, Cusack S, Kadlec J, Akhtar A: Structural analysis of the KANSL1/WDR5/KANSL2 complex reveals that WDR5 is required for efficient assembly and chromatin targeting of the NSL complex. Genes Dev 2014, 28: 929-942. Zhao X, Su J, Wang F, Liu D, Ding J, Yang Y, Conaway JW, Conaway RC, Cao L, Wu D, et al: Crosstalk between NSL histone acetyltransferase and MLL/SET complexes: NSL complex functions in promoting histone H3K4 di-methylation activity by MLL/SET complexes. PLoS Genet 2013, 9: e1003940. Bode D, Yu L, Tate P, Pardo M, Choudhary J: Characterization of Two Distinct Nucleosome Remodeling and Deacetylase (NuRD) Complex Assemblies in Embryonic Stem Cells. Mol Cell Proteomics 2016, 15: 878-891. Ee LS, McCannell KN, Tang Y, Fernandes N, Hardy WR, Green MR, Chu F, Fazzio TG: An Embryonic Stem Cell-Specific NuRD Complex Functions through Interaction with WDR5. Stem Cell Reports 2017, 8: 1488-1496. Beurton F, Stempor P, Caron M, Appert A, Dong Y, Chen RA, Cluet D, Coute Y, Herbette M, Huang N, et al: Physical and functional interaction between SET1/COMPASS complex component CFP-1 and a Sin3S HDAC complex in C. elegans. Nucleic Acids Res 2019, 47: 11164-11180. Simonet T, Dulermo R, Schott S, Palladino F: Antagonistic functions of SET-2/SET1 and HPL/HP1 proteins in C. elegans development. Dev Biol 2007, 312: 367-383. Fisher K, Southall SM, Wilson JR, Poulin GB: Methylation and demethylation activities of a C. elegans MLL-like complex attenuate RAS signalling. Dev Biol 2010, 341: 142-153. Li T, Kelly WG: A role for Set1/MLL-related components in epigenetic regulation of the Caenorhabditis elegans germ line. PLoS Genet 2011, 7: e1001349. Wang S, Fisher K, Poulin GB: Lineage specific trimethylation of H3 on lysine 4 during C. elegans early embryogenesis. Dev Biol 2011, 355: 227-238. Caron M, Gely L, Garvis S, Adrait A, Coute Y, Palladino F, Fabrizio P: Loss of SET1/COMPASS methyltransferase activity reduces lifespan and fertility in Caenorhabditis elegans. Life Sci Alliance 2022, 5 . Greer EL, Maures TJ, Ucar D, Hauswirth AG, Mancini E, Lim JP, Benayoun BA, Shi Y, Brunet A: Transgenerational epigenetic inheritance of longevity in Caenorhabditis elegans. Nature 2011, 479: 365-371. Wang S, Meyer DH, Schumacher B: H3K4me2 regulates the recovery of protein biosynthesis and homeostasis following DNA damage. Nat Struct Mol Biol 2020, 27: 1165-1177. Lee TW, David HS, Engstrom AK, Carpenter BS, Katz DJ: Repressive H3K9me2 protects lifespan against the transgenerational burden of COMPASS activity in C. elegans. Elife 2019, 8 . Zuryn S, Ahier A, Portoso M, White ER, Morin MC, Margueron R, Jarriault S: Transdifferentiation. Sequential histone-modifying activities determine the robustness of transdifferentiation. Science 2014, 345: 826-829. Abay-Norgaard S, Attianese B, Boreggio L, Salcini AE: Regulators of H3K4 methylation mutated in neurodevelopmental disorders control axon guidance in Caenorhabditis elegans. Development 2020, 147 . Kaser-Pebernard S, Muller F, Wicky C: LET-418/Mi2 and SPR-5/LSD1 cooperatively prevent somatic reprogramming of C. elegans germline stem cells. Stem Cell Reports 2014, 2: 547-559. Robert VJ, Mercier MG, Bedet C, Janczarski S, Merlet J, Garvis S, Ciosk R, Palladino F: The SET-2/SET1 histone H3K4 methyltransferase maintains pluripotency in the Caenorhabditis elegans germline. Cell Rep 2014, 9: 443-450. Ding W, Smulan LJ, Hou NS, Taubert S, Watts JL, Walker AK: s-Adenosylmethionine Levels Govern Innate Immunity through Distinct Methylation-Dependent Pathways. Cell Metab 2015, 22: 633-645. Brenner S: The genetics of Caenorhabditis elegans. Genetics 1974, 77: 71-94. Liu T, Rechtsteiner A, Egelhofer TA, Vielle A, Latorre I, Cheung MS, Ercan S, Ikegami K, Jensen M, Kolasinska-Zwierz P, et al: Broad chromosomal domains of histone modification patterns in C. elegans. Genome Res 2011, 21: 227-236. Egan B, Yuan CC, Craske ML, Labhart P, Guler GD, Arnott D, Maile TM, Busby J, Henry C, Kelly TK, et al: An Alternative Approach to ChIP-Seq Normalization Enables Detection of Genome-Wide Changes in Histone H3 Lysine 27 Trimethylation upon EZH2 Inhibition. PLoS One 2016, 11: e0166438. Ramirez F, Ryan DP, Gruning B, Bhardwaj V, Kilpert F, Richter AS, Heyne S, Dundar F, Manke T: deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res 2016, 44: W160-165. Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, Liu XS: Model-based analysis of ChIP-Seq (MACS). Genome Biol 2008, 9: R137. Gerstein MB, Lu ZJ, Van Nostrand EL, Cheng C, Arshinoff BI, Liu T, Yip KY, Robilotto R, Rechtsteiner A, Ikegami K, et al: Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project. Science 2010, 330: 1775-1787. Chen RA, Down TA, Stempor P, Chen QB, Egelhofer TA, Hillier LW, Jeffers TE, Ahringer J: The landscape of RNA polymerase II transcription initiation in C. elegans reveals promoter and enhancer architectures. Genome Res 2013, 23: 1339-1347. Janes J, Dong Y, Schoof M, Serizay J, Appert A, Cerrato C, Woodbury C, Chen R, Gemma C, Huang N, et al: Chromatin accessibility dynamics across C. elegans development and ageing. Elife 2018, 7 . Bolger AM, Lohse M, Usadel B: Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014, 30: 2114-2120. Kim D, Pertea G, Trapnell C, Pimentel H, Kelley R, Salzberg SL: TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol 2013, 14: R36. Anders S, Pyl PT, Huber W: HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 2015, 31: 166-169. Love MI, Huber W, Anders S: Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014, 15: 550. Orlando DA, Chen MW, Brown VE, Solanki S, Choi YJ, Olson ER, Fritz CC, Bradner JE, Guenther MG: Quantitative ChIP-Seq normalization reveals global modulation of the epigenome. Cell Rep 2014, 9: 1163-1170. Holdorf AD, Higgins DP, Hart AC, Boag PR, Pazour GJ, Walhout AJM, Walker AK: WormCat: An Online Tool for Annotation and Visualization of Caenorhabditis elegans Genome-Scale Data. Genetics 2020, 214: 279-294. Ayoub A, Park SH, Lee YT, Cho US, Dou Y: Regulation of MLL1 Methyltransferase Activity in Two Distinct Nucleosome Binding Modes. Biochemistry 2022, 61: 1-9. Park SH, Ayoub A, Lee YT, Xu J, Kim H, Zheng W, Zhang B, Sha L, An S, Zhang Y, et al: Cryo-EM structure of the human MLL1 core complex bound to the nucleosome. Nat Commun 2019, 10: 5540. Mittal A, Hobor F, Zhang Y, Martin SR, Gamblin SJ, Ramos A, Wilson JR: The structure of the RbBP5 beta-propeller domain reveals a surface with potential nucleic acid binding sites. Nucleic Acids Res 2018, 46: 3802-3812. Xiao Y, Bedet C, Robert VJ, Simonet T, Dunkelbarger S, Rakotomalala C, Soete G, Korswagen HC, Strome S, Palladino F: Caenorhabditis elegans chromatin-associated proteins SET-2 and ASH-2 are differentially required for histone H3 Lys 4 methylation in embryos and adult germ cells. Proc Natl Acad Sci U S A 2011, 108: 8305-8310. Wysocka J, Swigut T, Milne TA, Dou Y, Zhang X, Burlingame AL, Roeder RG, Brivanlou AH, Allis CD: WDR5 associates with histone H3 methylated at K4 and is essential for H3 K4 methylation and vertebrate development. Cell 2005, 121: 859-872. Fischer V, Plassard D, Ye T, Reina-San-Martin B, Stierle M, Tora L, Devys D: The related coactivator complexes SAGA and ATAC control embryonic stem cell self-renewal through acetyltransferase-independent mechanisms. Cell Rep 2021, 36: 109598. Shi X, Hong T, Walter KL, Ewalt M, Michishita E, Hung T, Carney D, Pena P, Lan F, Kaadige MR, et al: ING2 PHD domain links histone H3 lysine 4 methylation to active gene repression. Nature 2006, 442: 96-99. Li Q, Huang Y, Xu J, Mao F, Zhou B, Sun L, Basinski BW, Aksu M, Liu J, Dou Y, Rao RC: p53 inactivation unmasks histone methylation-independent WDR5 functions that drive self-renewal and differentiation of pluripotent stem cells. Stem Cell Reports 2021, 16: 2642-2658. Kulkarni SS, Khokha MK: WDR5 regulates left-right patterning via chromatin-dependent and -independent functions. Development 2018, 145 . Li T, Kelly WG: A role for WDR5 in TRA-1/Gli mediated transcriptional control of the sperm/oocyte switch in C. elegans. Nucleic Acids Res 2014, 42: 5567-5581. Huang Y, Jay KL, Huang AY, Wan J, Jangam SV, Chorin O, Rothschild A, Barel O, Mariani M, Iascone M, et al: Loss-of-function in RBBP5 results in a syndromic neurodevelopmental disorder associated with microcephaly. Genet Med 2024 : 101218. Kamath RS, Fraser AG, Dong Y, Poulin G, Durbin R, Gotta M, Kanapin A, Le Bot N, Moreno S, Sohrmann M, et al: Systematic functional analysis of the Caenorhabditis elegans genome using RNAi. Nature 2003, 421: 231-237. Mazzetto M, Gonzalez LE, Sanchez N, Reinke V: Characterization of the distribution and dynamics of chromatin states in the C. elegans germline reveals substantial H3K4me3 remodeling during oogenesis. Genome Res 2024, 34: 57-69. Zylicz JJ, Bousard A, Zumer K, Dossin F, Mohammad E, da Rocha ST, Schwalb B, Syx L, Dingli F, Loew D, et al: The Implication of Early Chromatin Changes in X Chromosome Inactivation. Cell 2019, 176: 182-197 e123. Pferdehirt RR, Kruesi WS, Meyer BJ: An MLL/COMPASS subunit functions in the C. elegans dosage compensation complex to target X chromosomes for transcriptional regulation of gene expression. Genes Dev 2011, 25: 499-515. Additional Declarations No competing interests reported. Supplementary Files SamsudinTableS1.xlsx SamsudinTableS2.xlsx SamsudinTableS3.xlsx SamsudinSupplfigure1.pdf Supplementary Figure 1. Effects of normalisation on H3K4 methylation profiles. (A) Heatmaps showing histone H3K4 methylation ChIP-seq signal intensities centred on TSS (±2 kb) in wild-type (N2), wdr-5(-) , and rbbp-5(-) embryos. For each genotype, pre-correction (raw) and post-correction (normalised) ChIP-seq signals are shown for H3K4me3, me2, and me1. SamsudinSupplfigure2.pdf Supplementary Figure 2. Benchmarking spike-in ChIP-seq datasets against modENCODE using PCA and Pearson correlation analysis. (A) Principal Component Analysis (PCA) of usable ChIP-seq tags from this study (N2) and public C. elegans datasets from modENCODE (R1, R2) for H3K4me1, H3K4me2, and H3K4me3. Samples cluster primarily by histone modification (color-coded) and by replicate, indicating high signal specificity and low technical noise. (B) Pearson correlation matrix of usable ChIP-seq tags shows high intra-group correlation, especially among replicates targeting the same modification. Hierarchical clustering groups samples by H3K4me1, H3K4me2, and H3K4me3, with datasets from this study (N2) and modENCODE (R1, R2) generally in strong agreement. SamsudinSupplfigure3.pdf Supplementary Figure 3. 2-way and 3-way Venn diagrams showing that whilst both WDR-5 and RBBP-5 are part of the SET/MLL complex, WDR-5 has additional regulatory activities. ( A - C ) 2-way Venn diagrams showing the overlap of mis-, up- and down-regulated genes between the rbbp-5(-) and wdr-5(-) single mutants . (D-F) 3-way Venn diagrams showing the overlap of mis-, up- and down-regulated between rbbp-5(-) , wdr-5(-) , and rbbp-5(-); wdr-5(-) mutants. Cite Share Download PDF Status: Published Journal Publication published 25 Mar, 2026 Read the published version in Epigenetics & Chromatin → Version 1 posted Editorial decision: Revision requested 18 Aug, 2025 Reviews received at journal 18 Aug, 2025 Reviews received at journal 13 Aug, 2025 Reviews received at journal 07 Aug, 2025 Reviewers agreed at journal 06 Aug, 2025 Reviewers agreed at journal 06 Aug, 2025 Reviewers agreed at journal 31 Jul, 2025 Reviewers invited by journal 30 Jul, 2025 Editor assigned by journal 30 Jul, 2025 Submission checks completed at journal 30 Jul, 2025 First submitted to journal 29 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7240678","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":494451955,"identity":"e09489ec-27b5-4565-999a-e24a29eac123","order_by":0,"name":"Nurulhafizah Binti Samsudin","email":"","orcid":"","institution":"University of Manchester","correspondingAuthor":false,"prefix":"","firstName":"Nurulhafizah","middleName":"Binti","lastName":"Samsudin","suffix":""},{"id":494451956,"identity":"520430d3-01dd-45de-ae13-17c02313f7da","order_by":1,"name":"Kate Fisher","email":"","orcid":"","institution":"University of Manchester","correspondingAuthor":false,"prefix":"","firstName":"Kate","middleName":"","lastName":"Fisher","suffix":""},{"id":494451957,"identity":"2395873c-f477-42ba-b4e6-6a545afd49ff","order_by":2,"name":"Gino B Poulin","email":"data:image/png;base64,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","orcid":"","institution":"University of Manchester","correspondingAuthor":true,"prefix":"","firstName":"Gino","middleName":"B","lastName":"Poulin","suffix":""}],"badges":[],"createdAt":"2025-07-29 08:08:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7240678/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7240678/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13072-026-00669-y","type":"published","date":"2026-03-25T16:11:42+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88266105,"identity":"454a5b17-c3fa-44e3-a72b-6e4192ea1f30","added_by":"auto","created_at":"2025-08-04 16:19:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1644538,"visible":true,"origin":"","legend":"\u003cp\u003eCryo-electron microscopy structure of a representative SET/MLL complex with experimental rationale and description of the spike-in ChIP-seq approach. \u003cstrong\u003e(A) \u003c/strong\u003eThe cryo-electron microscopy structure depicts the molecular surface of the core complex components WDR5, RBBP5, ASH2L, and the MLL3 catalytic module bound to nucleosome core particles containing mono-ubiquitinated H2BK120 (PDB: 6KIW; [21]). H2BK120ub1 acts as a trans-histone crosstalk signal to enhance H3K4 methylation. The complex adopts a Y-shaped conformation, with RBBP5 and WDR5 forming the arms. The complex rests flat on the nucleosome, contacting both DNA and core histones through RBBP5. RBBP5 anchors the complex to the nucleosome and physically interacts with DNA, histones, ubiquitin, and other complex components. In contrast, WDR5 bridges and organizes the MLL-RBBP5 interface. WDR5 can act as a context-dependent modulator, promoting H3K4 methylation in the MLL1 complex but acting repressively in the context of MLL3. \u003cstrong\u003e(B)\u003c/strong\u003e Schematic overview of the study objectives, which are to define i) the roles of RBBP-5 and WDR-5 in regulating H3K4 mono-, di-, and tri-methylation and ii) the downstream effects on gene expression, using spike-in ChIP-seq and RNA-seq approaches, respectively.\u003c/p\u003e","description":"","filename":"Samsudinfigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/7125a8d159def75a42166069.png"},{"id":88266106,"identity":"70b98cf7-f13b-4706-895d-e6cc4cdcd259","added_by":"auto","created_at":"2025-08-04 16:19:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1749890,"visible":true,"origin":"","legend":"\u003cp\u003eSpike-in ChIP-seq profiles reveal characteristic H3K4 methylation patterns at transcription start sites and active enhancers. (\u003cstrong\u003eA\u003c/strong\u003e) In wild-type \u003cem\u003eC. elegans\u003c/em\u003eembryos, H3K4me3, H3K4me2, and H3K4me1 exhibit distinct enrichment patterns around transcription start sites (TSS), consistent with previous studies [47, 51, 53]. Aggregate plots (top) and heatmaps (bottom) show ChIP-seq signal for H3K4me3 (red), H3K4me2 (blue), and H3K4me1 (green) centred on TSS (±2 kb). (\u003cstrong\u003eB\u003c/strong\u003e) Enhancers in wild-type embryos also show distinct H3K4 methylation profiles. Aggregate plots (top) and heatmaps (bottom) show H3K4me3, H3K4me2, and H3K4me1 ChIP-seq signal centred on enhancer midpoints (±2 kb).\u003c/p\u003e","description":"","filename":"Samsudinfigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/afba8c03618650d874537100.png"},{"id":88266110,"identity":"12bd85bd-4817-4e1d-92be-4ffe75a3c221","added_by":"auto","created_at":"2025-08-04 16:19:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1290144,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eRBBP-5 is required for bulk H3K4 methylation, whilst WDR-5 is critical for H3K4me3 deposition.\u003c/em\u003e\u003cstrong\u003e (A and B) \u003c/strong\u003eHeatmaps showing H3K4me3 ChIP-seq signal centred on transcription start sites (TSS) and enhancer midpoints (±2 kb) in wild-type (N2),\u003cem\u003e \u003c/em\u003e\u003cem\u003e\u003cstrong\u003ewdr-5(-)\u003c/strong\u003e\u003c/em\u003e, and \u003cem\u003e\u003cstrong\u003erbbp-5(-) \u003c/strong\u003e\u003c/em\u003eembryos. Both WDR-5 and RBBP-5 are critical for H3K4me3 deposition.\u003cstrong\u003e (C) \u003c/strong\u003eAggregate plots show mean ChIP-seq signal centred on H3K4me3 peaks (±5 kb) in wild-type (N2),\u003cem\u003e\u003cstrong\u003e wdr-5(-), \u003c/strong\u003e\u003c/em\u003eand \u003cem\u003e\u003cstrong\u003erbbp-5(-) \u003c/strong\u003e\u003c/em\u003eembryos. \u003cstrong\u003eGlobal \u003c/strong\u003eH3K4me3 enrichment is reduced in both \u003cem\u003e\u003cstrong\u003ewdr-5(-), \u003c/strong\u003e\u003c/em\u003eand \u003cem\u003e\u003cstrong\u003erbbp-5(-) \u003c/strong\u003e\u003c/em\u003emutants compared to wild type. (\u003cstrong\u003eD\u003c/strong\u003e) Schematic depiction of the WDR-5 and RBBP-5 positive contributions to H3K4me3.\u003c/p\u003e","description":"","filename":"Samsudinfigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/0403ec176d244dab0fc7946f.png"},{"id":88266883,"identity":"2d98271c-216e-4dc5-afb1-50a5c19f9867","added_by":"auto","created_at":"2025-08-04 16:27:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1470626,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eWDR-5 modulates H3K4me2 levels in a genomic feature-dependent manner. \u003c/em\u003e\u003cstrong\u003e(A and B) \u003c/strong\u003eHeatmaps showing H3K4me2 ChIP-seq signal centred on TSS and enhancer midpoints (±2 kb) in wild-type (N2),\u003cem\u003e \u003c/em\u003e\u003cem\u003e\u003cstrong\u003ewdr-5(-)\u003c/strong\u003e\u003c/em\u003e, and \u003cem\u003e\u003cstrong\u003erbbp-5(-) \u003c/strong\u003e\u003c/em\u003eembryos. WDR-5 contributes positively to H3K4me2 deposition at TSS but negatively at enhancers. In contrast, RBBP-5 is critical for H3K4me2 enrichment.\u003cstrong\u003e (C) \u003c/strong\u003eAggregate plots show mean ChIP-seq signal centred on H3K4me3 peaks (±5 kb) in wild-type (N2),\u003cem\u003e\u003cstrong\u003e wdr-5(-), \u003c/strong\u003e\u003c/em\u003eand \u003cem\u003e\u003cstrong\u003erbbp-5(-) \u003c/strong\u003e\u003c/em\u003eembryos. \u003cstrong\u003eGlobal \u003c/strong\u003eH3K4me2 enrichment is not affected in \u003cem\u003e\u003cstrong\u003ewdr-5(-) \u003c/strong\u003e\u003c/em\u003ecompared to wild type whereas it is heavily depleted in the \u003cem\u003e\u003cstrong\u003erbbp-5(-)\u003c/strong\u003e\u003c/em\u003e mutant. (\u003cstrong\u003eD\u003c/strong\u003e) Schematic depiction of the RBBP-5 positive contributions to H3K4me3 and H3K4me2. WDR-5 contributes positively to H3K4me3 and exhibits positive and negative modulatory activities towards H3K4me2.\u003c/p\u003e","description":"","filename":"Samsudinfigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/fbb61470e2361949a015ed73.png"},{"id":88266885,"identity":"8210a7d8-9875-41e6-82b6-7d9b478319a0","added_by":"auto","created_at":"2025-08-04 16:27:54","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2140667,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWDR-5 negatively impacts on H3K4me1. (A and B) \u003c/strong\u003eHeatmaps showing H3K4me1 ChIP-seq signal centred on TSS and enhancer midpoints (±2 kb) in wild-type (N2),\u003cem\u003e \u003c/em\u003e\u003cem\u003e\u003cstrong\u003ewdr-5(-)\u003c/strong\u003e\u003c/em\u003e, and \u003cem\u003e\u003cstrong\u003erbbp-5(-)\u003c/strong\u003e\u003c/em\u003e embryos. WDR-5 impacts negatively on to H3K4me1 levels at both TSS and enhancers. In contrast, RBBP-5 is critical for H3K4me1 enrichment.\u003cstrong\u003e (C) \u003c/strong\u003eAggregate plots show mean ChIP-seq signal centred on H3K4me1 peaks (±5 kb) in wild-type (N2),\u003cem\u003e\u003cstrong\u003e wdr-5(-),\u003c/strong\u003e\u003c/em\u003eand \u003cem\u003e\u003cstrong\u003erbbp-5(-) \u003c/strong\u003e\u003c/em\u003eembryos. \u003cstrong\u003eGlobal \u003c/strong\u003eH3K4me1 enrichment is increased in \u003cem\u003e\u003cstrong\u003ewdr-5(-) \u003c/strong\u003e\u003c/em\u003ecompared to wild type whereas it is heavily depleted in the \u003cem\u003e\u003cstrong\u003erbbp-5(-)\u003c/strong\u003e\u003c/em\u003e mutant. (\u003cstrong\u003eD\u003c/strong\u003e) Schematic depiction of the RBBP-5 positive contributions to H3K4me3, H3K4me2 and H3K4me1. WDR-5 contributes positively to H3K4me3, exhibits positive and negative modulatory activities towards H3K4me2, and impact negatively on the H3K4me1 levels.\u003c/p\u003e","description":"","filename":"Samsudinfigure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/52a463f2646845eeb2f497b1.png"},{"id":88266888,"identity":"e451dd28-511c-402c-b967-0c698ce5824f","added_by":"auto","created_at":"2025-08-04 16:27:55","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1151767,"visible":true,"origin":"","legend":"\u003cp\u003eChromosomal distribution of H3K4 methylation is differentially affected in the absence of WDR-5. Aggregate ChIP-seq signal plots show H3K4 methylation (±3 kb from TSS) for each chromosome in wild-type (N2) or \u003cem\u003e\u003cstrong\u003ewdr-5(-)\u003c/strong\u003e\u003c/em\u003e embryos as indicated.\u003cem\u003e \u003c/em\u003e\u003cstrong\u003e(A and B)\u003c/strong\u003e H3K4me3 levels at TSS are strongly reduced on autosomes in \u003cem\u003ewdr-5\u003c/em\u003e(-) embryos but are less affected on the X chromosome.\u003cstrong\u003e (C and D)\u003c/strong\u003e H3K4me2 levels are mildly reduced on autosomes but increased on the X chromosome in the absence of WDR-5.\u003cstrong\u003e (E and F)\u003c/strong\u003e H3K4me1 levels increase for all chromosomes in \u003cem\u003ewdr-5\u003c/em\u003e(-) embryos, with a more pronounced gain on the X chromosome.\u003cstrong\u003e (G)\u003c/strong\u003e Summary model illustrating the chromatin regulatory roles of RBBP-5 and WDR-5 in H3K4 methylation. RBBP-5 is required for deposition of all three methylation states. WDR-5 contributes positively to H3K4me3 deposition across the genome, promotes H3K4me2 on autosomes but represses it on the X chromosome, and restrains H3K4me1, especially on the X chromosome.\u003c/p\u003e","description":"","filename":"Samsudinfigure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/77adb61fc935adf6bbb76895.png"},{"id":88266116,"identity":"3db4db41-a1a0-4b7b-9e9f-8b1f8ba283e4","added_by":"auto","created_at":"2025-08-04 16:19:55","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":872400,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWDR-5 impacts the transcriptome more profoundly than RBBP-5.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA \u003c/strong\u003eand\u003cstrong\u003e B\u003c/strong\u003e) Volcano plots showing differentially expressed genes (DEG) in \u003cem\u003ewdr-5\u003c/em\u003e(-) and \u003cem\u003erbbp-5\u003c/em\u003e(-) embryos compared to wild-type. DEG (red dots) were defined as having \u0026gt;2-fold change and adjusted \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05. Loss of WDR-5 results in widespread dysregulation (2269 upregulated, 1108 downregulated genes), while RBBP-5 loss leads to a more limited response (661 upregulated, 60 downregulated genes).\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eC \u003c/strong\u003eand\u003cstrong\u003e D\u003c/strong\u003e) MA plots showing DEG (red) plotted against log10 baseMean expression. Data distribute symmetrically along the y-axis zero line, indicating no systemic bias introduced by DESeq2 modelling. (\u003cstrong\u003eE \u003c/strong\u003eand\u003cstrong\u003eF\u003c/strong\u003e) Violin and box plots showing baseline (wild-type) expression levels for up-regulated, down-regulated, and un-regulated genes in each mutant. Down-regulated genes tend to have higher baseline expression in wild type than up- or un-regulated genes. Up-regulated genes tend to have a lower baseline expression in wild type than down- or un-regulated genes. All three groups for both mutants are statistically different (p\u0026lt; 0.01) using the Mann-Whitney U test.\u003c/p\u003e","description":"","filename":"Samsudinfigure7.png","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/0db5b012400d057cf78725a9.png"},{"id":88266119,"identity":"66933277-20df-4e88-a6fd-b9f8c3ea4657","added_by":"auto","created_at":"2025-08-04 16:19:55","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":579392,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWDR-5 regulates gene expression independently of H3K4 methylation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA-C\u003c/strong\u003e) Experimental rationale for generating an \u003cem\u003erbbp-5\u003c/em\u003e(-); \u003cem\u003ewdr-5\u003c/em\u003e(-) double mutant to assess whether transcriptional changes in \u003cem\u003ewdr-5\u003c/em\u003e(-) are due to persistent H3K4 methylation. (\u003cstrong\u003eA\u003c/strong\u003e) In the absence of RBBP-5, H3K4 methylation is abolished. (\u003cstrong\u003eB\u003c/strong\u003e) In the absence of WDR-5, H3K4me2 is erroneously distributed but still present whereas H3K4me1 levels are increased. Parallel activities associated with Histone acetylation and deacetylation (HAT and HDAC) are depicted by the side line. (\u003cstrong\u003eC\u003c/strong\u003e) Two hypotheses: if WDR-5 acts through H3K4 methylation only, the double mutant should resemble \u003cem\u003erbbp-5\u003c/em\u003e(-); if WDR-5 also has parallel activities independent of H3K4 methylation, the double mutant should resemble \u003cem\u003ewdr-5\u003c/em\u003e(-). The double mutant embryos lacking both RBBP-5 and WDR-5 show transcriptomic deregulation similar to the single \u003cem\u003ewdr-5(-)\u003c/em\u003e mutant, thus favouring the model whereby H3K4 methylation independent activities are implicated. (\u003cstrong\u003eD\u003c/strong\u003e) Volcano plot shows DEG in \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e embryos relative to wild type. There are 2553 significantly up-regulated genes versus 1129 down-regulated genes. (\u003cstrong\u003eE\u003c/strong\u003e) Hierarchical clustering reveals that the transcriptomes of the \u003cem\u003ewdr-5(-)\u003c/em\u003e single mutant and the \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e double mutants are highly similar. Heatmap shows z-score normalised expression values for DEG across the \u003cem\u003erbbp-5(-)\u003c/em\u003eand \u003cem\u003ewdr-5(-)\u003c/em\u003e single mutants and the double \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e mutant. Genes are clustered by expression pattern across the three genotypes.\u003c/p\u003e","description":"","filename":"Samsudinfigure8.png","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/61fac867af42994b171851ca.png"},{"id":88266112,"identity":"56e2f910-2d34-4916-b7e6-bf07e6e49c67","added_by":"auto","created_at":"2025-08-04 16:19:54","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":286211,"visible":true,"origin":"","legend":"\u003cp\u003eMost functional categories of DEG are shared between the single mutants and the \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e double mutant. Bubble plot shows the distribution of DEG across WormCat2.0 functional categories for each genotype. Circle size corresponds to the number of DEG per category and colour reflects enrichment score as indicated. The outlined categories are shared across all three geneotypes.\u003c/p\u003e","description":"","filename":"Samsudinfigure9.png","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/46e968bb3248f893a01a4f38.png"},{"id":105754976,"identity":"764945dc-fb85-4f08-a6d1-9998c126072b","added_by":"auto","created_at":"2026-03-30 16:23:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":15994519,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/017fdaaa-2ed8-4b13-9e9b-ad92ca0a6bbd.pdf"},{"id":88266887,"identity":"ce4eee0d-818d-4ee5-b35e-353c821e8ced","added_by":"auto","created_at":"2025-08-04 16:27:54","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3047142,"visible":true,"origin":"","legend":"","description":"","filename":"SamsudinTableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/50539c6ce494cb1454f6a42a.xlsx"},{"id":88266108,"identity":"43b33589-b53d-4d91-ae00-b45c6a2cbd48","added_by":"auto","created_at":"2025-08-04 16:19:54","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":9310,"visible":true,"origin":"","legend":"","description":"","filename":"SamsudinTableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/c83e9836e61865724ac9b4ea.xlsx"},{"id":88266886,"identity":"97acf786-d894-4cf2-9737-60d991c1ab29","added_by":"auto","created_at":"2025-08-04 16:27:54","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":10819,"visible":true,"origin":"","legend":"","description":"","filename":"SamsudinTableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/0b0da3b5b6bbd563b426b84d.xlsx"},{"id":88266124,"identity":"08eb5320-3463-4b01-95f3-cb36489a4a2f","added_by":"auto","created_at":"2025-08-04 16:19:55","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2988582,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects of normalisation on H3K4 methylation profiles. (A)\u003c/strong\u003e Heatmaps showing histone H3K4 methylation ChIP-seq signal intensities centred on TSS (±2 kb) in wild-type (N2), \u003cem\u003ewdr-5(-)\u003c/em\u003e, and \u003cem\u003erbbp-5(-)\u003c/em\u003e embryos. For each genotype, pre-correction (raw) and post-correction (normalised) ChIP-seq signals are shown for H3K4me3, me2, and me1.\u003c/p\u003e","description":"","filename":"SamsudinSupplfigure1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/f0c49321083ddf43d89e8189.pdf"},{"id":88266125,"identity":"11002ad4-3824-4c38-b58e-cb24eebfd4fe","added_by":"auto","created_at":"2025-08-04 16:19:55","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":57286,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 2.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBenchmarking spike-in ChIP-seq datasets against modENCODE using PCA and Pearson correlation analysis. (A)\u003c/strong\u003e Principal Component Analysis (PCA) of usable ChIP-seq tags from this study (N2) and public \u003cem\u003eC. elegans\u003c/em\u003edatasets from modENCODE (R1, R2) for H3K4me1, H3K4me2, and H3K4me3. Samples cluster primarily by histone modification (color-coded) and by replicate, indicating high signal specificity and low technical noise. \u003cstrong\u003e(B) \u003c/strong\u003ePearson correlation matrix of usable ChIP-seq tags shows high intra-group correlation, especially among replicates targeting the same modification. Hierarchical clustering groups samples by H3K4me1, H3K4me2, and H3K4me3, with datasets from this study (N2) and modENCODE (R1, R2) generally in strong agreement.\u003c/p\u003e","description":"","filename":"SamsudinSupplfigure2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/a9fae7fad7a79b1800f33380.pdf"},{"id":88266117,"identity":"eccf30b6-9996-48b5-b481-997ebf87692f","added_by":"auto","created_at":"2025-08-04 16:19:55","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":89453,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 3.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2-way and 3-way Venn diagrams showing that whilst both WDR-5 and RBBP-5 are part of the SET/MLL complex, WDR-5 has additional regulatory activities. \u003c/strong\u003e\u003cem\u003e(\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e-\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) 2-way \u003c/em\u003eVenn diagrams showing the overlap of mis-, up- and down-regulated genes between the \u003cem\u003erbbp-5(-)\u003c/em\u003e and \u003cem\u003ewdr-5(-) single mutants\u003c/em\u003e. (\u003cstrong\u003eD\u003c/strong\u003e-\u003cstrong\u003eF\u003c/strong\u003e) 3-way Venn diagrams showing the overlap of mis-, up- and down-regulated between \u003cem\u003erbbp-5(-)\u003c/em\u003e, \u003cem\u003ewdr-5(-)\u003c/em\u003e, and \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e mutants.\u003c/p\u003e","description":"","filename":"SamsudinSupplfigure3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7240678/v1/4003f67fdcbc660f9e52efc1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"WDR-5 exhibits H3K4 methylation-independent activity during embryonic development in C. elegans","fulltext":[{"header":"Background","content":"\u003cp\u003eThe chromatin landscape is shaped by the organisation of nucleosomes within the confined space of the nucleus. The resulting epigenome facilitates the organisation of RNA polymerase II into transcription factories and regulatory hubs that help establish and maintain gene expression patterns during development [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Histones, in association with DNA form nucleosomes, the fundamental units of chromatin. Initially described as barriers to transcription, decades of chromatin research have since revealed that nucleosomes play far more nuanced roles, acting through post-translational modifications that can either promote or repress transcription [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOne of these modifications occurs on Histone 3 at Lysine 4 (H3K4me) and involves the covalent attachment of up to three methyl groups to form mono-, di-, or tri-methylated forms (H3K4me1, me2, and me3). These three modifications have distinct patterns of deposition and are broadly associated with transcriptionally active genes [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. H3K4me3 is the most notable of these modifications as it is strongly correlated with active Transcription Start Sites (TSS) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. H3K4me3 can regulate initiation and elongation during proximal-promoter pause-release of RNA-pol II [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e–\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In addition to these roles, studies have shown that H3K4me2/me3 can generate bivalent domains when coupled with H3K27me2/me3. These bivalent domains regulate expression of developmental genes, which are initially repressed but poised to later resolve their transcriptional state [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In addition, H3K4me2 can also mediate non-coding RNA-mediated repression of Hox genes [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], whilst both H3K4me2 and H3K4me3 can suppress cryptic transcription [\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e–\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Furthermore, enrichment in H3K4me1 together with H3K27 acetylation define transcriptionally active enhancers [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Collectively, these studies suggest that alterations in H3K4 methylation may compromise transcriptional states by perturbing both activating and repressive mechanisms.\u003c/p\u003e\u003cp\u003eH3K4 methylation is catalysed by the evolutionarily conserved SET/COMPASS and MLL (Mixed Lineage Leukaemia) complexes [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e–\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] referred to hereafter collectively as the SET/MLL complex. These complexes consist of SET domain-containing methyltransferases (KMT2 enzymes) and a core scaffolding complex that together transfer methyl groups from the universal donor S-adenosylmethionine to H3K4, generating H3K4me1/me2/me3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA;[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]). Notably, the number of KMT2 enzymes increases with species complexity: one in \u003cem\u003eS. cerevisiae\u003c/em\u003e; two in \u003cem\u003eC. elegans\u003c/em\u003e; three in \u003cem\u003eDrosophila\u003c/em\u003e; and six in mammals [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These enzymes form distinct SET/MLL sub-complexes that share core components but also include specific co-factors. The main core subunits are WDR5, RBBP5, ASH2L, and DPY30, which associate with co-factors such as CFP1 or Menin to form SET or MLL complexes, respectively [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Interestingly, WDR5 is also found in other chromatin-modifying complexes containing HAT or HDAC activities [\u003cspan additionalcitationids=\"CR26 CR27 CR28 CR29 CR30 CR31\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e–\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], challenging the attribution of WDR5-dependent transcriptional changes solely to its role in H3K4 methylation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn \u003cem\u003eC. elegans\u003c/em\u003e, the SET/MLL complex is comprised of two KMT2 enzymes: SET-2, a SET orthologue [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] and SET-16, an MLL-like enzyme [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The scaffolding subunits WDR-5, ASH-2, and RBBP-5 are highly conserved across species [\u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e–\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Independent loss of these scaffolding components alters H3K4 methylation and leads to phenotypes including altered lifespan [\u003cspan additionalcitationids=\"CR38 CR39\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e–\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], erroneous hindgut-to-neuron transdifferentiation [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], increased RAS signalling in vulval cells [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], axon guidance defects [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] and disrupted germ cell pluripotency [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. SET-16-dependent H3K4me3 also contributes to innate immunity [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Despite the clear roles of these components in H3K4 methylation, a comparative, quantitative analysis of their individual contributions has been lacking.\u003c/p\u003e\u003cp\u003eHerein, we determined the contribution of WDR-5 and RBBP-5 towards all three H3K4 methylation states using spike-in ChIP-seq on \u003cem\u003eC. elegans\u003c/em\u003e embryos (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). We found that WDR-5 primarily prevents the deposition of tri-methyl groups at H3K4. In contrast, the absence of RBBP-5 abrogates all three states of H3K4 methylation. RNA-seq analysis show that \u003cem\u003erbbp-5(-)\u003c/em\u003e mutant embryos displayed fewer transcriptomic changes than \u003cem\u003ewdr-5(-)\u003c/em\u003e embryos (721 versus 3377 Differentially Expressed Genes, respectively). Furthermore, the transcriptome of the \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e double mutant, which lacks H3K4 methylation, closely resembled the \u003cem\u003ewdr-5(-)\u003c/em\u003e single mutant. This indicates that gene expression changes in the \u003cem\u003ewdr-5(-)\u003c/em\u003e mutant occur largely independently of H3K4 methylation. Together, our findings reveal that WDR-5 is required for H3K4me3 deposition and that it acts in parallel to H3K4 methylation to regulate gene expression.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eStrains and general maintenance\u003c/p\u003e\u003cp\u003e\u003cem\u003eC. elegans\u003c/em\u003e strains were maintained at 20°C and as described in Brenner et al. [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Strains used in this study are: N2 (wild type), \u003cem\u003ewdr-5.1(ok1417) III\u003c/em\u003e (RB1304), \u003cem\u003erbbp-5(tm3463) II\u003c/em\u003e, and the double \u003cem\u003erbbp-5(tm3463) II; wdr-5.1(ok1417) III\u003c/em\u003e (OL76).\u003c/p\u003e\u003cp\u003eEmbryonic preparation on large solid media plates for spike-in ChIP-seq\u003c/p\u003e\u003cp\u003eSynchronised population of embryos were prepared on solid NGM media from bleached young adult hermaphrodites. These adults were harvested from two rounds of amplifications; each performed on 20 Corning tissue culture dishes (245 x 245 mm) that were seeded with synchronised L1 (larval stage 1) obtained from bleaching large numbers of gravid adults. To obtain these large populations of worms, dishes were seeded with 0.5 ml of 20x OP50 stock and left to dry for at least two days before use. 20 dishes per strain were seeded with synchronised L1s: ~1,000 L1s for N2 (wild type), ~ 2,000 L1s for \u003cem\u003ewdr-5(-)\u003c/em\u003e, and ~ 3,000 L1s for \u003cem\u003erbbp-5(-)\u003c/em\u003e. When the next generation reached L4 stage, all worms were harvested and transferred onto 20 new dishes to prevent starvation and mature adults were bleached to generate large populations of synchronised L1s, which were all re-seeded onto 20 dishes. These L1s were grown to obtain young adults, a stage reached after 54h for N2 (wild type), and 64h for \u003cem\u003ewdr-5(-)\u003c/em\u003e and \u003cem\u003erbbp-5(-)\u003c/em\u003e. Following bleaching of these adults, embryos were collected on sucrose gradients and re-suspended in 47 ml of M9 buffer and 2.8 ml of 37% formaldehyde solution (~ 2% final). Embryos were placed on a shaker (50 rpm) at room temperature for 30 minutes, then spun down and the pellets quenched by adding 50 ml of 100 mM Tris buffer (pH 7.5) to stop the fixation process. Fixed embryos were spun down and washed twice with 50 ml M9, then 10 ml FA buffer (50 mM HEPES/KOH pH 7.5, 1 mM EDTA pH 8, 1% Triton x-100, 0.1% sodium deoxycholate, 150 mM NaCl) containing protease inhibitor cocktail was added to the pellet. Between 200 µl and 500 µl of packed embryos can be obtained from this method. Next, an aliquot of 5 µl of embryos for each genotype was taken out, treated with methanol, and stained with DAPI for scoring on standard 2% agarose pad with a coverslip (store at -20°C). The embryo preparations used for N2 (wild type), \u003cem\u003ewdr-5(-)\u003c/em\u003e, and \u003cem\u003erbbp-5(-)\u003c/em\u003e were comparable: 20–40% at \u0026lt; 28-cell stages; 20–27% between 28-cell and 100-cell stages; 32–52% at pre-coma stage; and 0–4% at coma stage or beyond. Then, samples were prepared as previously described [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Briefly, embryo pellets were re-suspended in a total of 1.5 ml FA buffer (50 mM HEPES/KOH pH 7.5, 1 mM EDTA pH 8, 1% Triton x-100, 0.1% sodium deoxycholate, 150 mM NaCl) with protease inhibitor cocktail. Embryos were dounced 40 times on ice using a pastel B homogeniser and aliquoted in 250 µl into six 1.5 ml microtubes. Sonication was performed using the Bioruptor UCD-200 (30 sec ON, 30 sec OFF) with ultrasonic wave output at HIGH for three 5 min cycles. Between cycles, the samples were cooled in a dry ice/ethanol bath for 5 sec. A small aliquot was kept to verify the DNA size on a 1.5% agarose gel showing enrichment between 400–600 bp. In the meantime, the samples were snap frozen and kept at -80°C. The frozen embryonic samples were then shipped to ActiveMotif on dry ice to perform the spike-in ChIP-seq procedure [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Briefly, about 5% of \u003cem\u003eD. melanogaster\u003c/em\u003e was added to \u003cem\u003eC. elegans\u003c/em\u003e embryo chromatin. 0.4 µg of the anti-H2Av antibody (AM39715) was used to immunoprecipitate \u003cem\u003eD. melanogaster\u003c/em\u003e chromatin from each reaction, which is then used as a reference for normalisation. The antibodies are from ActiveMotif and are: anti-H3K4me1 (AM39297), anti-H3K4me2 (AM39141), and anti-H3K4me3 (AM39159).\u003c/p\u003e\u003cp\u003eSpike-in ChIP-seq libraries and data processing\u003c/p\u003e\u003cp\u003eIllumina sequencing libraries were prepared from the ChIP and input DNAs by the standard consecutive enzymatic steps of end-polishing, dA-addition, and adaptor ligation. After a final PCR amplification step, the resulting DNA libraries were quantified and sequenced on Illumina’s NextSeq 500 (75 nt reads, single end).\u003c/p\u003e\u003cp\u003eAll genomic analyses were performed using the \u003cem\u003eCaenorhabditis elegans\u003c/em\u003e genome build WS220 (ce10). ChIP-seq reads were aligned to the ce10 genome using Bowtie2 v2.3.4 and processed with Samtools v1.9 and Picard. Duplicate reads were removed using MarkDuplicates, and mitochondrial reads were filtered out. To account for GC content bias, we applied computeGCBias and correctGCBias from DeepTools (v3.5.6) [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Normalisation by downsampling was carried out on the GC-corrected BAM files using Picard and spike-in normalisation factors applied. Final normalised coverage tracks (BigWigs) were generated from the downsampled, GC-corrected BAM files using bamCoverage with CPM normalisation and a bin size of 10 bp. These tracks were used in all downstream DeepTools analyses, including heatmaps, metagene plots, and principal component analysis.\u003c/p\u003e\u003cp\u003ePeak locations for overall genomic enrichment were determined using the MACS2 algorithm (v2.2.9.1) with an effective genome size of 9.3×10⁷ and a q-value threshold of 0.05 [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. For H3K4me2 and H3K4me3, broad peaks were called using default model-based parameters with a broad cutoff of 0.1. For H3K4me1, due to poor model estimation, peaks were called using ‘nomodel’ mode and a fixed fragment extension size of 147 bp. All peak calls were performed on GC-bias-corrected BAM files using matched input controls.\u003c/p\u003e\u003cp\u003eThe N2 wild type data were benchmarked against modEncode publicly available early embryonic ChIP-seq dataset (H3K4me1 repl 1: GSM1217259 repl 2: GSM1217260 input: GSM1217261; H3K4me2 repl 1: GSM1206344 repl 2: GSM1206345 input: GSM1206346; H3K4me3 repl 1: GSM1206368 repl 2: GSM1206369 input: GSM1206370) [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo compare H3K4me1, H3K4me2, and H3K4me3 levels between wild type and mutants, Transcription Start Sites (TSS) generated by Chen et al. [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] and active enhancers mapped by Janes et al. [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] were used. Normalised bigWig files containing ChIP-seq signal coverage were analysed using Deeptools [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The bigWig files corresponding to wild-type (WT), \u003cem\u003ewdr-5(-)\u003c/em\u003e, and \u003cem\u003erbbp-5(-)\u003c/em\u003e conditions were GC bias-corrected and normalised. BED files defining TSS and enhancer regions were uploaded for further processing.\u003c/p\u003e\u003cp\u003eEmbryonic preparations for RNA-seq\u003c/p\u003e\u003cp\u003eSynchronised populations of adult worms for N2, \u003cem\u003erbbp-5(-)\u003c/em\u003e, \u003cem\u003ewdr-5(-)\u003c/em\u003e and \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e were grown on 10 cm plates. Young adults were bleached and the embryos scored for developmental stages using DIC microscopy. The populations were consistently between ~ 25–30% at 28–100 cell stage, ~ 45–55% at pre-coma stage, and ~ 5–15% at late embryogenesis stages, roughly matching the spike-in ChIP-seq samples. Three biological replicates were prepared per genotype. Total RNA was extracted using TRIzol (Invitrogen) and stored at -80°C until sent for analysis to the Genomic core facility at the Faculty of Biology, Medicine and Health (University of Manchester).\u003c/p\u003e\u003cp\u003eRNA-seq libraries and analysis\u003c/p\u003e\u003cp\u003eRNA-seq libraries were generated using the TruSeq Stranded mRNA Sample Preparation Kit (Illumina), followed by 101 × 101 bp paired-end sequencing on the Illumina HiSeq platform. Across 12 libraries, an average of ~ 208\u0026nbsp;million paired-end reads per sample were obtained (range: 100–422\u0026nbsp;million), with an average alignment rate of 94% to the \u003cem\u003eC. elegans\u003c/em\u003e reference genome (ce10). Mate 1 and mate 2 reads were balanced across all samples, indicating high-quality libraries. FastQC and Trimmomatic [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] were used for quality control and adapter trimming. Reads were aligned using TopHat 2.1.0 [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], and gene-level quantification was performed using HTSeq [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] with the c_elegans WS220.annotations.gtf annotation file. Differentially expressed genes (DEGs) were identified using DESeq2 [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], applying thresholds of fold change \u0026gt; 2 and adjusted p-value \u0026lt; 0.05 with a cut-off for read counts set at 50 as detected in wild type and/or mutant samples.\u003c/p\u003e\u003cp\u003eCalculation of Net Transcriptome Change Percent\u003c/p\u003e\u003cp\u003eTo assess the global directional impact of transcriptomic changes in mutants relative to wild type, we calculated the Net Transcriptome Change Percent by integrating the direction of expression change (log₂ fold change) with the level of gene expression (baseMean) for differentially expressed genes (DEGs). Only DEGs passing thresholds for both adjusted p-value and fold change were included in this analysis. For each mis-regulated gene, the baseMean (mean normalised expression across all samples) was multiplied by its log₂-transformed fold change (log₂FC). The contributions of all mis-regulated genes were summed to produce the Net Directional Change. The baseMean values for all DEGs were summed to calculate the Total BaseMean, representing the total transcript abundance for all mis-regulated genes irrespective of regulation direction. The Net Transcriptome Change Percent was calculated by expressing the Net Directional Change as a proportion of the Total BaseMean and multiplied by 100. This metric provides a global estimate of the directional bias in transcriptomic change, expressed as a percentage of the total mis-regulated gene expression. Negative percentages indicate net down-regulation; positive percentages indicate net up-regulation.\u003c/p\u003e\u003cp\u003eStatistical test on the Violin plots\u003c/p\u003e\u003cp\u003eWe tested whether genes classified as up-regulated, down-, or mis-regulated in a mutant background tend to have different expression levels \u003cb\u003ein wild type\u003c/b\u003e compared to unregulated genes, using the baseMeanA metric (representing average wild-type expression). We performed a Mann-Whitney U test, also called a Pairwise Wilcoxon rank-sum tests, applied to log2-transformed baseMeanA values to assess distributional shifts across categories.\u003c/p\u003e\u003cp\u003eChIP-seq and RNA-seq data access\u003c/p\u003e\u003cp\u003eThe ChIP-seq data have been deposited in the GEO repository under ID code GSE94639 and RNA-seq data have been deposited in the ArrayExpress repository under ID code E-MTAB-15080.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eBenchmarking H3K4 mono- and multi-methylation spike-in ChIP-seq data\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTo assess the \u003cem\u003ein vivo\u003c/em\u003e contributions of RBBP-5 and WDR-5 to H3K4 methylation, we performed spike-in ChIP-seq on \u003cem\u003eC. elegans\u003c/em\u003e embryos for H3K4me1, H3K4me2, and H3K4me3. This approach enables accurate comparison across genotypes, especially important given the expected global reduction in H3K4 methylation in \u003cem\u003erbbp-5(-)\u003c/em\u003e and \u003cem\u003ewdr-5(-)\u003c/em\u003e mutants. Spike-in normalisation is critical for such cross-genotype comparisons in ChIP-seq [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. In our study, we used \u003cem\u003eDrosophila\u003c/em\u003e chromatin and an antibody against the \u003cem\u003eDrosophila\u003c/em\u003e-specific histone variant H2Av to normalise for technical variability during the ChIP process [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Normalisation analysis confirmed its necessity, particularly in the \u003cem\u003erbbp-5(-)\u003c/em\u003e background for all three marks (H3K4me3/me2/me1; Suppl. Figure\u0026nbsp;1). In the \u003cem\u003ewdr-5(-)\u003c/em\u003e mutant, the normalisation also produced a reduction in the number of usable tags, but to a lesser extent than in the \u003cem\u003erbbp-5(-)\u003c/em\u003e mutant. By contrast, the wild type samples were either unaffected (H3K4me3/me2) or only marginally affected (H3K4me1) by normalisation (Suppl. Figure\u0026nbsp;1). To benchmark data quality, we compared our spike-in ChIP-seq datasets with publicly available modENCODE H3K4me1/2/3 data [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Principal Component Analysis (PCA) demonstrated clustering of our samples alongside modENCODE replicates according to H3K4 methylation state (Suppl. Figure\u0026nbsp;2A), confirming reproducibility. Pearson correlation analysis further validated high concordance between our data and the modENCODE datasets (Suppl. Figure\u0026nbsp;2B). Finally, we assessed the genomic distribution of H3K4 methylation at transcription start sites (TSS) of protein-coding genes and at active enhancers [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. As expected, H3K4me3 was enriched at TSS (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), whilst H3K4me1 showed characteristic enhancer enrichment (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), consistent with published data [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Together, these analyses confirm that our spike-in ChIP-seq data are robust, well-normalised, and comparable to established datasets.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eRBBP-5 is required for bulk H3K4 methylation, whilst WDR-5 is critical for H3K4me3\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTo establish the contribution to H3K4 methylation from these scaffolding components, we compared the deposition of H3K4 mono- and multi-methylation between wild-type (N2) and the \u003cem\u003ewdr-5(-)\u003c/em\u003e and \u003cem\u003erbbp-5(-)\u003c/em\u003e mutants. We first analysed H3K4me3 enrichment. In the absence of RBBP-5, H3K4me3 was almost completely lost at both TSS and enhancers (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and B). In \u003cem\u003ewdr-5(-)\u003c/em\u003e embryos, H3K4me3 levels were also markedly reduced at TSS and enhancers, although the depletion was less severe than in the \u003cem\u003erbbp-5(-)\u003c/em\u003e mutant (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and B). Global H3K4me3 levels mirrored these findings, with the most pronounced reduction observed in the absence of RBBP-5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). We also constructed a schematic model to illustrate the relative contributions of RBBP-5 and WDR-5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe next examined H3K4me2 deposition. As with H3K4me3, the absence of RBBP-5 resulted in an almost complete loss of H3K4me2 enrichment at both TSS and enhancers (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and B). In contrast, the effects of WDR-5 loss on H3K4me2 were context-dependent: H3K4me2 levels were reduced at TSS, but increased at enhancers (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and B). These opposing changes appeared to balance each other, resulting in no significant difference in the global H3K4me2 levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). We incorporated these context-specific effects into our schematic model to reflect the nuanced contribution of WDR-5 to H3K4me2 deposition (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFinally, we analysed H3K4me1 levels. RBBP-5 was essential for H3K4me1 deposition at both TSS and enhancers (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA and B), a requirement that also held true at the global level (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). In contrast, the absence of WDR-5 led to an increase in H3K4me1 at TSS, enhancers, and globally (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u0026ndash;C). This accumulation may result from impaired progression to higher methylation states, leading to the build-up of H3K4me1. These data were integrated into our schematic to illustrate the distinct roles of RBBP-5 and WDR-5 in regulating H3K4me1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). Overall, these results show that RBBP-5 is essential for all H3K4 methylation states, whereas WDR-5 is primarily required for H3K4me3. These findings highlight the distinct roles of these scaffolding components in shaping the H3K4 methylation landscape.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eChromosome X is differentially impacted by the absence of WDR-5 relative to autosomes\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTo address whether the absence of WDR-5 affects each chromosome similarly, we analysed H3K4 methylation enrichment at TSS for each chromosome individually. In wild type, the chromosomes with highest levels of H3K4me3 levels were chromosomes I and III, whilst chromosomes II and IV displayed intermediate levels, and chromosomes X and V showed the lowest levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). We examined how this chromosomal hierarchy of H3K4me3 levels was affected in the \u003cem\u003ewdr-5(-)\u003c/em\u003e mutant. As expected, we found a striking reduction, but chromosome X was not as profoundly affected (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). We next analysed H3K4me2 levels and found that chromosomes clustered similarly to the H3K4me3 analysis with high and intermediate levels still being represented by chromosome I and III and chromosome II and IV, respectively. However, relative H3K4me2 levels increased on chromosome X (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Interestingly, in the absence of WDR-5, autosomes exhibited a reduction in H3K4me2 enrichment, but the chromosome X displayed a robust increase (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). We then analysed the levels of H3K4me1, and found that in wild type, chromosome X was among the chromosomes with the highest and most characteristic H3K4me1 enrichment (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). As expected, in the \u003cem\u003ewdr-5(-)\u003c/em\u003e deletion, all chromosomes displayed an increase in the levels of H3K4me1, but the chromosome X was the most affected (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). Together these findings reveal that while WDR-5 is broadly required for H3K4 multi-methylation across the autosomes, chromosome X appears to be subject to a WDR-5-independent regulatory mechanism that sustains or even enhances H3K4 multi-methylation in its absence (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eWDR-5 has a greater impact on the transcriptome than RBBP-5\u003c/em\u003e\u003c/p\u003e\u003cp\u003eGiven the distinct effects of WDR-5 and RBBP-5 on H3K4 methylation, we next asked how these differences would be reflected at the transcriptome level. To address this, we performed RNA-seq on staged embryos and identified differentially expressed genes (DEG) relative to wild type.\u003c/p\u003e\u003cp\u003eIn \u003cem\u003ewdr-5(-)\u003c/em\u003e embryos, we identified 3377 DEG, comprising 1108 down-regulated genes and 2269 up-regulated genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). In contrast, the \u003cem\u003erbbp-5(-)\u003c/em\u003e mutant exhibited only 721 DEGs, with 60 down-regulated and 661 up-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The predominance of up-regulated genes was to an extent unexpected, given the association of H3K4 methylation with active transcription, though previous studies have also noted this prevalence. Our findings are therefore consistent with prior transcriptomic analyses comparing \u003cem\u003ewdr-5(-)\u003c/em\u003e and \u003cem\u003eset-2(-)\u003c/em\u003e mutants in dissected \u003cem\u003eC. elegans\u003c/em\u003e gonads. The authors similarly reported a bias towards up-regulation [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. However, another study using \u003cem\u003eset-2\u003c/em\u003e mutants in early embryos reported a more balanced distribution of down- and up-regulated genes [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eUpon re-analysing this early embryonic dataset [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] with both a two-fold change cutoff and padj\u0026thinsp;\u0026lt;\u0026thinsp;0.05, we found an enrichment for up-regulated genes (587 up versus 203 down; Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e), which is in line with our findings. To assess the performance of DESeq2 normalisation, we generated MA plots for each comparison (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC, D). Data points were centred around log2 fold change\u0026thinsp;=\u0026thinsp;0 at low expression levels, confirming successful normalisation. The data are also consistent with the effects observed on the \u003cem\u003ewdr-5(-)\u003c/em\u003e and \u003cem\u003erbbp-5(-)\u003c/em\u003e respective transcriptomes, whereby more genes are up-regulated than down-regulated in both mutants.\u003c/p\u003e\u003cp\u003eWe next asked whether down-regulated genes in the mutants tend to be highly expressed in wild type, given the known association between highly expressed genes and H3K4 methylation. To assess this point, we separated the data into down-, up-, and un-regulated genes and plotted their associated levels of expression in wild type (baseMean wild type) for each corresponding mutant (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE and F). Indeed, down-regulated genes in each mutant exhibited significantly higher expression in wild type than up-regulated genes and un-regulated genes (pval\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suggesting that these down-regulated genes are more likely to represent direct WDR-5 or RBBP-5 targets (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE, F).\u003c/p\u003e\u003cp\u003eFinally, to assess the global impact of WDR-5 and RBBP-5 loss on their respective transcriptomes, we quantified the net directional change in expression across all DEG. This metric integrates both the direction (log2 fold change) and magnitude (baseMean) of expression changes to summarise transcriptomic shifts. In \u003cem\u003ewdr-5(-)\u003c/em\u003e embryos, we observed a net change of -28%, indicating an overall decrease in gene expression among mis-regulated genes (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). In contrast, \u003cem\u003erbbp-5(-)\u003c/em\u003e embryos showed a milder net change of -9% (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). Thus, while both mutants exhibit more up- than down-regulated genes, the overall net effect is a reduction in number of transcripts. This effect is more pronounced in \u003cem\u003ewdr-5(-)\u003c/em\u003e, consistent with its broader transcriptomic perturbation (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA and B).\u003c/p\u003e\u003cp\u003e\u003cem\u003eWDR-5 exhibits H3K4 methylation-independent functions impacting on gene expression\u003c/em\u003e\u003c/p\u003e\u003cp\u003eWe next asked the question whether the large number of DEG in \u003cem\u003ewdr-5(-)\u003c/em\u003e could be attributed to the persistence of H3K4me1, H3K4me2 or residual H3K4me3. To test this, we generated an \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e double mutant, in which H3K4 methylation is unlikely because of the absence of RBBP-5. We made two predictions as to how the \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e double mutant would affect transcription (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA-C). One is that the transcriptomic profile of the double mutant will resemble that of \u003cem\u003erbbp-5(-)\u003c/em\u003e alone (~\u0026thinsp;700 DEG) because the perturbations in the \u003cem\u003ewdr-5(-)\u003c/em\u003e transcriptome are explained by persistent H3K4me1, H3K4me2 or residual H3K4me3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC; left panel). The second possibility is that the transcriptomic profile of the double mutant will mirror the \u003cem\u003ewdr-5(-)\u003c/em\u003e transcriptome (~\u0026thinsp;3000 DEG) because the absence of RBBP-5 does not interfere with WDR-5 parallel activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC; right panel). It turns out that the \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e double mutant exhibited 3682 DEG (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eD), a number comparable to the \u003cem\u003ewdr-5(-)\u003c/em\u003e single mutant (3377 DEGs; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Clustering analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eE) and Venn diagrams (Suppl. Figure\u0026nbsp;3) confirmed substantial overlap between the DEG of the double and \u003cem\u003ewdr-5(-)\u003c/em\u003e mutants. Moreover, a large proportion of the DEG identified in \u003cem\u003erbbp-5(-)\u003c/em\u003e were also found in \u003cem\u003ewdr-5(-)\u003c/em\u003e and in the double mutant, consistent with both proteins acting within the SET/MLL complex (Suppl. Figure\u0026nbsp;3). However, the broader transcriptional changes observed in the absence of WDR-5 (even when H3K4 methylation is abolished) strongly suggest that WDR-5 has additional functions beyond promoting H3K4 methylation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe next compared Gene Ontology categories between the three datasets using WormCat 2.0 [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] and found that many of the categories are shared between the single \u003cem\u003ewdr-5(-)\u003c/em\u003e and \u003cem\u003erbbp-5(-)\u003c/em\u003e mutants and the double \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e mutant, indicating that those functions such as neuronal and stress response are likely regulated, at least in part, by H3K4 methylation (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Other WormCat categories (transcription factors, cytoskeleton, and cilia) are shared between the single \u003cem\u003ewdr-5(-)\u003c/em\u003e mutant and the double \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e mutant and these are likely regulated by WDR-5 parallel activity. Taken together, these data show that the transcriptomes of the single \u003cem\u003ewdr-5(-)\u003c/em\u003e and the double \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e mutants share a high degree of similarity, indicating that WDR-5 can affect gene expression independently of H3K4 methylation during \u003cem\u003eC. elegans\u003c/em\u003e embryogenesis.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study shows that WDR-5 and RBBP-5 have distinctive roles in the deposition of methyl marks at H3K4. WDR-5 facilitates H3K4 tri-methylation, whilst RBBP-5 is necessary for mono- and multi-methylation. These functions align with cryo-EM structural studies showing that RBBP5 plays a central role in nucleating the MLL1 core complex on the nucleosome, and engaging both its DNA and histone surfaces to orient the complex [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan additionalcitationids=\"CR61\" citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Our data are also largely consistent with other studies performed on \u003cem\u003eC. elegans\u003c/em\u003e embryos [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. We also show that WDR-5 has intricate and more subtle functions; its absence reduces H3K4 methylation more prominently on autosomes than on the sex chromosome and the effects on deposition of H3K4me2 can be either positive or negative depending on the genomic features involved. Crucially, we were able to functionally demonstrate that WDR-5 exhibits H3K4 methylation-independent activity by analysing the transcriptome of a double mutant between \u003cem\u003erbbp-5(-)\u003c/em\u003e and \u003cem\u003ewdr-5(-)\u003c/em\u003e and comparing it with the single mutants.\u003c/p\u003e\u003cp\u003eOur study shows that WDR-5 has profound impacts on gene expression that are independent of its role in H3K4 methylation. WDR-5 is found physically associated with additional chromatin complexes. These \u0026lsquo;moonlighting\u0026rsquo; activities are likely explaining our results whereby the alterations in the transcriptome of the \u003cem\u003ewdr-5(-)\u003c/em\u003e mutant are more profound than in the \u003cem\u003erbbp-5(-)\u003c/em\u003e transcriptome. This conclusion is based on our results from the double \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e mutant showing that most of these \u003cem\u003ewdr-5(-)\u003c/em\u003e alterations in gene expression are independent of H3K4 methylation, since H3K4 methylation is abrogated without RBBP-5. Thus, our work supports the proposal by Guarnaccia et al. that WDR-5 acts as a multi-functional hub in the nucleus [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWDR5 was first characterised in mammals as a core component of the H3K4 methylation complex [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. However, it was later found in other complexes notably the NSL (Non-Specific Lethal) and ATAC (Ada Two A Containing) histone acetyltransferase complexes [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. WDR5 can also be found in histone deacetylases complexes such as RPD3 HDAC in yeast (or mSin3a-HDAC1 in mammals) and the NuRD complex [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. ING2, a component of the sSin3a-HDAC1, interacts via its PHD domain with H3K4me3 to stimulate deacetylation and repress transcription [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. In yeast, it was found that H3K4me2/me3 can recruit RPD3 HDAC to repress cryptic transcription [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In \u003cem\u003eC. elegans\u003c/em\u003e, WDR-5 is found within the Sin3S HDAC repressive complex [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], which is similar to RPD3 HDAC in yeast and sSin3a-HDAC1 in mammals. Interestingly, work in other species support an H3K4 methylation-independent role for WDR5. WDR5 point mutations defective in H3K4 methylation could still rescue specific phenotypes such as mouse embryonic stem cells self-renewal defects and de-repression of germ cell specific genes [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e] as well as left-right patterning of the heart in Xenopus [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], indicating that H3K4 methylation-independent activity is conserved in vertebrates. Thus, WDR-5 appears to act as a multi-functional hub regulating both activation and context-dependent repression of transcription via H3K4 methylation as well as histone acetylation and deacetylation. This promiscuous activity most likely explains the effects on the \u003cem\u003ewdr-5(-)\u003c/em\u003e transcriptome reported herein. However, whether and how any of these activities are privileged over others remains to be elucidated.\u003c/p\u003e\u003cp\u003eIn contrast to WDR-5, RBBP-5 is critical and specific to the deposition of H3K4 methyl groups. Concordant with our work, a study investigating crosstalk between the NSL and SET/MLL complexes in \u003cem\u003eDrosophila\u003c/em\u003e has shown that depletion of RBBP5 affects H3K4me2 deposition but not H4K16 acetylation, indicating that RBBP5 is not directly affecting histone acetylation, whereas WDR5 inactivation can affect both H3K4 methylation and H4K16 acetylation [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In addition, a \u003cem\u003eC. elegans\u003c/em\u003e study investigating masculinisation of the germline found that this phenotype arises in the absence of WDR-5 but not in the absence of RBBP-5, indicating that WDR-5 has H3K4 methylation-independent activity but not RBBP-5 [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. It is also interesting to note that loss-of-function mutations in RBBP-5 in humans have recently been identified and associated with neurodevelopmental disorder, short stature and microcephaly [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e], highlighting the importance of H3K4 methylation for neuronal function.\u003c/p\u003e\u003cp\u003eOur analysis has also revealed a chromosomal hierarchy in H3K4me3 enrichment at transcription start sites, which closely mirrors the pattern of phenotypic enrichment observed through systematic RNAi screening [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. Specifically, chromosomes I and III exhibit the highest levels of H3K4me3, followed by chromosomes II and IV, and with chromosomes V and X showing the lowest enrichment. This pattern is consistent with previous findings showing that chromosomes I and III are relatively enriched for active chromatin marks, including H3K4 methylation, whereas chromosomes V and X are comparatively depleted [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. One possible explanation linking H3K4me3 enrichment to RNAi phenotypic outcomes is that genes which are robustly transcribed (and therefore more heavily marked by H3K4me3) are more likely to yield observable phenotypes when knocked down by RNAi. Although the mechanisms coordinating transcriptional regulation at the chromosome-wide level remain poorly understood, it is plausible that differential H3K4me3 enrichment reflects the partitioning of chromosomes into distinct chromatin environments during early embryogenesis. Higher levels of H3K4me3 on chromosomes I and III may indicate a more open, transcriptionally permissive architecture, possibly maintained through large-scale domain organisation or preferential spatial positioning within the nucleus. Conversely, the lower H3K4me3 levels on chromosomes V and X could reflect sequestration into less active chromatin territories. Notably, data from a recent \u003cem\u003eC. elegans\u003c/em\u003e study investigating partitioning of chromatin states in the germlines has also revealed that transcriptionally active domains (marked by high H3K4me3 and H3K36me3) follow a similar chromosomal hierarchy [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. These chromosome-wide biases in chromatin accessibility and transcriptional competence may underlie the observed correspondence between H3K4me3 and RNAi phenotype enrichment.\u003c/p\u003e\u003cp\u003eOur chromosome-level analysis also shows that H3K4me1 enrichment and distribution at TSS on chromosome X are distinct from those on autosomes. It is therefore tempting to speculate that H3K4me1 could play a role on chromosome X to dampen transcription. Alternatively, as shown during the early stages of X chromosome inactivation in mammals [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e], elevated H3K4me1 levels may reflect reduced transcription and the incomplete conversion into H3K4me2 and H3K4me3. There is also the possibility that the SET/MLL complex could play a role in regulating the dosage compensation (DC) complex. It has been shown that DPY-30, an additional scaffolding component of the SET/MLL complex, is also present in the DC complex [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. The authors show that DPY-30 and ASH-2 are found at a subset of sites known to be critical for dosage compensation. Since ASH-2 knockdown does not affect the recruitment and function of the DC complex, it seems that the SET/MLL complex would act downstream or in parallel. It is plausible that the co-localisation of the DC and SET/MLL complexes at the same DC binding sites prevents enrichment of H3K4me3 and thereby increases the levels of H3K4me1, which would be consistent with our findings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eTogether, our findings establish that WDR-5 and RBBP-5 exert distinct functions in chromatin regulation, with WDR-5 having a broader influence on gene expression through mechanisms most likely beyond H3K4 methylation. This highlights WDR-5 as a versatile regulatory scaffold in chromatin biology. Future work will be needed to determine how WDR-5\u0026rsquo;s roles across different chromatin-modifying complexes are coordinated, and whether specific chromatin contexts favour particular functions over others. Defining the precise interactome of WDR-5 \u003cem\u003ein vivo\u003c/em\u003e will help clarify these mechanisms and further understanding of its roles in development and disease.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate: Not applicable.\u003c/p\u003e\n\u003cp\u003eConsent for publication: Not applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe ChIP-seq data have been deposited in the GEO repository under ID code GSE94639 and RNA-seq data have been deposited in the ArrayExpress repository under ID code E-MTAB-15080.\u003c/p\u003e\n\u003cp\u003eCompeting interests:\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding:\u003c/p\u003e\n\u003cp\u003eThis work was in part supported by the Biotechnology and Biological Sciences Research Council (BB/J014834/1) and by the Wellcome Trust [097820/Z/11/Z].\u0026nbsp;Some strains were provided by the CGC (Caenorhabditis Genetics Center). The CGC is funded by NIH Office of Research Infrastructure Programs [P40 OD010440].\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions:\u003c/p\u003e\n\u003cp\u003eThe conception and experimental design, the analysis and interpretation of the data, and writing of the manuscript was performed by GP. NBS and KF have performed laboratory work necessary for acquisition of the data.\u003c/p\u003e\n\u003cp\u003eAcknowledgements:\u003c/p\u003e\n\u003cp\u003eWe thank A. Hayes, his team, L. Zeef and P. Wang of the Bioinformatics and Genomic Technologies Core Facilities at the University of Manchester for providing support regarding RNA-seq experiments. Dr. Siyao Wang, former PhD student from the Poulin lab, for contributing towards the generation of the double \u003cem\u003erbbp-5(-); wdr-5(-)\u003c/em\u003e mutant. Our colleagues Prof. Andy Sharrocks and Dr. Alan Whitmarsh for providing valuable advice on the manuscript.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePalacio M, Taatjes DJ: \u003cstrong\u003eMerging Established Mechanisms with New Insights: Condensates, Hubs, and the Regulation of RNA Polymerase II Transcription.\u003c/strong\u003e \u003cem\u003eJ Mol Biol \u003c/em\u003e2022, \u003cstrong\u003e434:\u003c/strong\u003e167216.\u003c/li\u003e\n\u003cli\u003eBannister AJ, Kouzarides T: \u003cstrong\u003eRegulation of chromatin by histone modifications.\u003c/strong\u003e \u003cem\u003eCell Res \u003c/em\u003e2011, \u003cstrong\u003e21:\u003c/strong\u003e381-395.\u003c/li\u003e\n\u003cli\u003eKouzarides T: \u003cstrong\u003eChromatin modifications and their function.\u003c/strong\u003e \u003cem\u003eCell \u003c/em\u003e2007, \u003cstrong\u003e128:\u003c/strong\u003e693-705.\u003c/li\u003e\n\u003cli\u003eWang H, Helin K: \u003cstrong\u003eRoles of H3K4 methylation in biology and disease.\u003c/strong\u003e \u003cem\u003eTrends Cell Biol \u003c/em\u003e2024.\u003c/li\u003e\n\u003cli\u003eBarski A, Cuddapah S, Cui K, Roh TY, Schones DE, Wang Z, Wei G, Chepelev I, Zhao K: \u003cstrong\u003eHigh-resolution profiling of histone methylations in the human genome.\u003c/strong\u003e \u003cem\u003eCell \u003c/em\u003e2007, \u003cstrong\u003e129:\u003c/strong\u003e823-837.\u003c/li\u003e\n\u003cli\u003eGuenther MG, Levine SS, Boyer LA, Jaenisch R, Young RA: \u003cstrong\u003eA chromatin landmark and transcription initiation at most promoters in human cells.\u003c/strong\u003e \u003cem\u003eCell \u003c/em\u003e2007, \u003cstrong\u003e130:\u003c/strong\u003e77-88.\u003c/li\u003e\n\u003cli\u003eHu S, Song A, Peng L, Tang N, Qiao Z, Wang Z, Lan F, Chen FX: \u003cstrong\u003eH3K4me2/3 modulate the stability of RNA polymerase II pausing.\u003c/strong\u003e \u003cem\u003eCell Res \u003c/em\u003e2023, \u003cstrong\u003e33:\u003c/strong\u003e403-406.\u003c/li\u003e\n\u003cli\u003eSantos-Rosa H, Schneider R, Bannister AJ, Sherriff J, Bernstein BE, Emre NC, Schreiber SL, Mellor J, Kouzarides T: \u003cstrong\u003eActive genes are tri-methylated at K4 of histone H3.\u003c/strong\u003e \u003cem\u003eNature \u003c/em\u003e2002, \u003cstrong\u003e419:\u003c/strong\u003e407-411.\u003c/li\u003e\n\u003cli\u003eWang H, Fan Z, Shliaha PV, Miele M, Hendrickson RC, Jiang X, Helin K: \u003cstrong\u003eH3K4me3 regulates RNA polymerase II promoter-proximal pause-release.\u003c/strong\u003e \u003cem\u003eNature \u003c/em\u003e2023, \u003cstrong\u003e615:\u003c/strong\u003e339-348.\u003c/li\u003e\n\u003cli\u003eBernstein BE, Mikkelsen TS, Xie X, Kamal M, Huebert DJ, Cuff J, Fry B, Meissner A, Wernig M, Plath K, et al: \u003cstrong\u003eA bivalent chromatin structure marks key developmental genes in embryonic stem cells.\u003c/strong\u003e \u003cem\u003eCell \u003c/em\u003e2006, \u003cstrong\u003e125:\u003c/strong\u003e315-326.\u003c/li\u003e\n\u003cli\u003eRinn JL, Kertesz M, Wang JK, Squazzo SL, Xu X, Brugmann SA, Goodnough LH, Helms JA, Farnham PJ, Segal E, Chang HY: \u003cstrong\u003eFunctional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs.\u003c/strong\u003e \u003cem\u003eCell \u003c/em\u003e2007, \u003cstrong\u003e129:\u003c/strong\u003e1311-1323.\u003c/li\u003e\n\u003cli\u003eBriggs SD, Bryk M, Strahl BD, Cheung WL, Davie JK, Dent SY, Winston F, Allis CD: \u003cstrong\u003eHistone H3 lysine 4 methylation is mediated by Set1 and required for cell growth and rDNA silencing in Saccharomyces cerevisiae.\u003c/strong\u003e \u003cem\u003eGenes Dev \u003c/em\u003e2001, \u003cstrong\u003e15:\u003c/strong\u003e3286-3295.\u003c/li\u003e\n\u003cli\u003eKim T, Buratowski S: \u003cstrong\u003eDimethylation of H3K4 by Set1 recruits the Set3 histone deacetylase complex to 5\u0026apos; transcribed regions.\u003c/strong\u003e \u003cem\u003eCell \u003c/em\u003e2009, \u003cstrong\u003e137:\u003c/strong\u003e259-272.\u003c/li\u003e\n\u003cli\u003ePinskaya M, Gourvennec S, Morillon A: \u003cstrong\u003eH3 lysine 4 di- and tri-methylation deposited by cryptic transcription attenuates promoter activation.\u003c/strong\u003e \u003cem\u003eEMBO J \u003c/em\u003e2009, \u003cstrong\u003e28:\u003c/strong\u003e1697-1707.\u003c/li\u003e\n\u003cli\u003eRyu HY: \u003cstrong\u003eHistone Modification Pathways Suppressing Cryptic Transcription.\u003c/strong\u003e \u003cem\u003eEpigenomes \u003c/em\u003e2024, \u003cstrong\u003e8\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eCreyghton MP, Cheng AW, Welstead GG, Kooistra T, Carey BW, Steine EJ, Hanna J, Lodato MA, Frampton GM, Sharp PA, et al: \u003cstrong\u003eHistone H3K27ac separates active from poised enhancers and predicts developmental state.\u003c/strong\u003e \u003cem\u003eProc Natl Acad Sci U S A \u003c/em\u003e2010, \u003cstrong\u003e107:\u003c/strong\u003e21931-21936.\u003c/li\u003e\n\u003cli\u003eHeintzman ND, Hon GC, Hawkins RD, Kheradpour P, Stark A, Harp LF, Ye Z, Lee LK, Stuart RK, Ching CW, et al: \u003cstrong\u003eHistone modifications at human enhancers reflect global cell-type-specific gene expression.\u003c/strong\u003e \u003cem\u003eNature \u003c/em\u003e2009, \u003cstrong\u003e459:\u003c/strong\u003e108-112.\u003c/li\u003e\n\u003cli\u003eMiller T, Krogan NJ, Dover J, Erdjument-Bromage H, Tempst P, Johnston M, Greenblatt JF, Shilatifard A: \u003cstrong\u003eCOMPASS: a complex of proteins associated with a trithorax-related SET domain protein.\u003c/strong\u003e \u003cem\u003eProc Natl Acad Sci U S A \u003c/em\u003e2001, \u003cstrong\u003e98:\u003c/strong\u003e12902-12907.\u003c/li\u003e\n\u003cli\u003eNagy PL, Griesenbeck J, Kornberg RD, Cleary ML: \u003cstrong\u003eA trithorax-group complex purified from Saccharomyces cerevisiae is required for methylation of histone H3.\u003c/strong\u003e \u003cem\u003eProc Natl Acad Sci U S A \u003c/em\u003e2002, \u003cstrong\u003e99:\u003c/strong\u003e90-94.\u003c/li\u003e\n\u003cli\u003eRoguev A, Schaft D, Shevchenko A, Pijnappel WW, Wilm M, Aasland R, Stewart AF: \u003cstrong\u003eThe Saccharomyces cerevisiae Set1 complex includes an Ash2 homologue and methylates histone 3 lysine 4.\u003c/strong\u003e \u003cem\u003eEMBO J \u003c/em\u003e2001, \u003cstrong\u003e20:\u003c/strong\u003e7137-7148.\u003c/li\u003e\n\u003cli\u003eXue H, Yao T, Cao M, Zhu G, Li Y, Yuan G, Chen Y, Lei M, Huang J: \u003cstrong\u003eStructural basis of nucleosome recognition and modification by MLL methyltransferases.\u003c/strong\u003e \u003cem\u003eNature \u003c/em\u003e2019, \u003cstrong\u003e573:\u003c/strong\u003e445-449.\u003c/li\u003e\n\u003cli\u003eShilatifard A: \u003cstrong\u003eThe COMPASS family of histone H3K4 methylases: mechanisms of regulation in development and disease pathogenesis.\u003c/strong\u003e \u003cem\u003eAnnu Rev Biochem \u003c/em\u003e2012, \u003cstrong\u003e81:\u003c/strong\u003e65-95.\u003c/li\u003e\n\u003cli\u003eWenzel D, Palladino F, Jedrusik-Bode M: \u003cstrong\u003eEpigenetics in C. elegans: facts and challenges.\u003c/strong\u003e \u003cem\u003eGenesis \u003c/em\u003e2011, \u003cstrong\u003e49:\u003c/strong\u003e647-661.\u003c/li\u003e\n\u003cli\u003eSze CC, Shilatifard A: \u003cstrong\u003eMLL3/MLL4/COMPASS Family on Epigenetic Regulation of Enhancer Function and Cancer.\u003c/strong\u003e \u003cem\u003eCold Spring Harb Perspect Med \u003c/em\u003e2016, \u003cstrong\u003e6\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eGuarnaccia AD, Tansey WP: \u003cstrong\u003eMoonlighting with WDR5: A Cellular Multitasker.\u003c/strong\u003e \u003cem\u003eJ Clin Med \u003c/em\u003e2018, \u003cstrong\u003e7\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eDou Y, Milne TA, Tackett AJ, Smith ER, Fukuda A, Wysocka J, Allis CD, Chait BT, Hess JL, Roeder RG: \u003cstrong\u003ePhysical association and coordinate function of the H3 K4 methyltransferase MLL1 and the H4 K16 acetyltransferase MOF.\u003c/strong\u003e \u003cem\u003eCell \u003c/em\u003e2005, \u003cstrong\u003e121:\u003c/strong\u003e873-885.\u003c/li\u003e\n\u003cli\u003eMendjan S, Taipale M, Kind J, Holz H, Gebhardt P, Schelder M, Vermeulen M, Buscaino A, Duncan K, Mueller J, et al: \u003cstrong\u003eNuclear pore components are involved in the transcriptional regulation of dosage compensation in Drosophila.\u003c/strong\u003e \u003cem\u003eMol Cell \u003c/em\u003e2006, \u003cstrong\u003e21:\u003c/strong\u003e811-823.\u003c/li\u003e\n\u003cli\u003eDias J, Van Nguyen N, Georgiev P, Gaub A, Brettschneider J, Cusack S, Kadlec J, Akhtar A: \u003cstrong\u003eStructural analysis of the KANSL1/WDR5/KANSL2 complex reveals that WDR5 is required for efficient assembly and chromatin targeting of the NSL complex.\u003c/strong\u003e \u003cem\u003eGenes Dev \u003c/em\u003e2014, \u003cstrong\u003e28:\u003c/strong\u003e929-942.\u003c/li\u003e\n\u003cli\u003eZhao X, Su J, Wang F, Liu D, Ding J, Yang Y, Conaway JW, Conaway RC, Cao L, Wu D, et al: \u003cstrong\u003eCrosstalk between NSL histone acetyltransferase and MLL/SET complexes: NSL complex functions in promoting histone H3K4 di-methylation activity by MLL/SET complexes.\u003c/strong\u003e \u003cem\u003ePLoS Genet \u003c/em\u003e2013, \u003cstrong\u003e9:\u003c/strong\u003ee1003940.\u003c/li\u003e\n\u003cli\u003eBode D, Yu L, Tate P, Pardo M, Choudhary J: \u003cstrong\u003eCharacterization of Two Distinct Nucleosome Remodeling and Deacetylase (NuRD) Complex Assemblies in Embryonic Stem Cells.\u003c/strong\u003e \u003cem\u003eMol Cell Proteomics \u003c/em\u003e2016, \u003cstrong\u003e15:\u003c/strong\u003e878-891.\u003c/li\u003e\n\u003cli\u003eEe LS, McCannell KN, Tang Y, Fernandes N, Hardy WR, Green MR, Chu F, Fazzio TG: \u003cstrong\u003eAn Embryonic Stem Cell-Specific NuRD Complex Functions through Interaction with WDR5.\u003c/strong\u003e \u003cem\u003eStem Cell Reports \u003c/em\u003e2017, \u003cstrong\u003e8:\u003c/strong\u003e1488-1496.\u003c/li\u003e\n\u003cli\u003eBeurton F, Stempor P, Caron M, Appert A, Dong Y, Chen RA, Cluet D, Coute Y, Herbette M, Huang N, et al: \u003cstrong\u003ePhysical and functional interaction between SET1/COMPASS complex component CFP-1 and a Sin3S HDAC complex in C. elegans.\u003c/strong\u003e \u003cem\u003eNucleic Acids Res \u003c/em\u003e2019, \u003cstrong\u003e47:\u003c/strong\u003e11164-11180.\u003c/li\u003e\n\u003cli\u003eSimonet T, Dulermo R, Schott S, Palladino F: \u003cstrong\u003eAntagonistic functions of SET-2/SET1 and HPL/HP1 proteins in C. elegans development.\u003c/strong\u003e \u003cem\u003eDev Biol \u003c/em\u003e2007, \u003cstrong\u003e312:\u003c/strong\u003e367-383.\u003c/li\u003e\n\u003cli\u003eFisher K, Southall SM, Wilson JR, Poulin GB: \u003cstrong\u003eMethylation and demethylation activities of a C. elegans MLL-like complex attenuate RAS signalling.\u003c/strong\u003e \u003cem\u003eDev Biol \u003c/em\u003e2010, \u003cstrong\u003e341:\u003c/strong\u003e142-153.\u003c/li\u003e\n\u003cli\u003eLi T, Kelly WG: \u003cstrong\u003eA role for Set1/MLL-related components in epigenetic regulation of the Caenorhabditis elegans germ line.\u003c/strong\u003e \u003cem\u003ePLoS Genet \u003c/em\u003e2011, \u003cstrong\u003e7:\u003c/strong\u003ee1001349.\u003c/li\u003e\n\u003cli\u003eWang S, Fisher K, Poulin GB: \u003cstrong\u003eLineage specific trimethylation of H3 on lysine 4 during C. elegans early embryogenesis.\u003c/strong\u003e \u003cem\u003eDev Biol \u003c/em\u003e2011, \u003cstrong\u003e355:\u003c/strong\u003e227-238.\u003c/li\u003e\n\u003cli\u003eCaron M, Gely L, Garvis S, Adrait A, Coute Y, Palladino F, Fabrizio P: \u003cstrong\u003eLoss of SET1/COMPASS methyltransferase activity reduces lifespan and fertility in Caenorhabditis elegans.\u003c/strong\u003e \u003cem\u003eLife Sci Alliance \u003c/em\u003e2022, \u003cstrong\u003e5\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eGreer EL, Maures TJ, Ucar D, Hauswirth AG, Mancini E, Lim JP, Benayoun BA, Shi Y, Brunet A: \u003cstrong\u003eTransgenerational epigenetic inheritance of longevity in Caenorhabditis elegans.\u003c/strong\u003e \u003cem\u003eNature \u003c/em\u003e2011, \u003cstrong\u003e479:\u003c/strong\u003e365-371.\u003c/li\u003e\n\u003cli\u003eWang S, Meyer DH, Schumacher B: \u003cstrong\u003eH3K4me2 regulates the recovery of protein biosynthesis and homeostasis following DNA damage.\u003c/strong\u003e \u003cem\u003eNat Struct Mol Biol \u003c/em\u003e2020, \u003cstrong\u003e27:\u003c/strong\u003e1165-1177.\u003c/li\u003e\n\u003cli\u003eLee TW, David HS, Engstrom AK, Carpenter BS, Katz DJ: \u003cstrong\u003eRepressive H3K9me2 protects lifespan against the transgenerational burden of COMPASS activity in C. elegans.\u003c/strong\u003e \u003cem\u003eElife \u003c/em\u003e2019, \u003cstrong\u003e8\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eZuryn S, Ahier A, Portoso M, White ER, Morin MC, Margueron R, Jarriault S: \u003cstrong\u003eTransdifferentiation. Sequential histone-modifying activities determine the robustness of transdifferentiation.\u003c/strong\u003e \u003cem\u003eScience \u003c/em\u003e2014, \u003cstrong\u003e345:\u003c/strong\u003e826-829.\u003c/li\u003e\n\u003cli\u003eAbay-Norgaard S, Attianese B, Boreggio L, Salcini AE: \u003cstrong\u003eRegulators of H3K4 methylation mutated in neurodevelopmental disorders control axon guidance in Caenorhabditis elegans.\u003c/strong\u003e \u003cem\u003eDevelopment \u003c/em\u003e2020, \u003cstrong\u003e147\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eKaser-Pebernard S, Muller F, Wicky C: \u003cstrong\u003eLET-418/Mi2 and SPR-5/LSD1 cooperatively prevent somatic reprogramming of C. elegans germline stem cells.\u003c/strong\u003e \u003cem\u003eStem Cell Reports \u003c/em\u003e2014, \u003cstrong\u003e2:\u003c/strong\u003e547-559.\u003c/li\u003e\n\u003cli\u003eRobert VJ, Mercier MG, Bedet C, Janczarski S, Merlet J, Garvis S, Ciosk R, Palladino F: \u003cstrong\u003eThe SET-2/SET1 histone H3K4 methyltransferase maintains pluripotency in the Caenorhabditis elegans germline.\u003c/strong\u003e \u003cem\u003eCell Rep \u003c/em\u003e2014, \u003cstrong\u003e9:\u003c/strong\u003e443-450.\u003c/li\u003e\n\u003cli\u003eDing W, Smulan LJ, Hou NS, Taubert S, Watts JL, Walker AK: \u003cstrong\u003es-Adenosylmethionine Levels Govern Innate Immunity through Distinct Methylation-Dependent Pathways.\u003c/strong\u003e \u003cem\u003eCell Metab \u003c/em\u003e2015, \u003cstrong\u003e22:\u003c/strong\u003e633-645.\u003c/li\u003e\n\u003cli\u003eBrenner S: \u003cstrong\u003eThe genetics of Caenorhabditis elegans.\u003c/strong\u003e \u003cem\u003eGenetics \u003c/em\u003e1974, \u003cstrong\u003e77:\u003c/strong\u003e71-94.\u003c/li\u003e\n\u003cli\u003eLiu T, Rechtsteiner A, Egelhofer TA, Vielle A, Latorre I, Cheung MS, Ercan S, Ikegami K, Jensen M, Kolasinska-Zwierz P, et al: \u003cstrong\u003eBroad chromosomal domains of histone modification patterns in C. elegans.\u003c/strong\u003e \u003cem\u003eGenome Res \u003c/em\u003e2011, \u003cstrong\u003e21:\u003c/strong\u003e227-236.\u003c/li\u003e\n\u003cli\u003eEgan B, Yuan CC, Craske ML, Labhart P, Guler GD, Arnott D, Maile TM, Busby J, Henry C, Kelly TK, et al: \u003cstrong\u003eAn Alternative Approach to ChIP-Seq Normalization Enables Detection of Genome-Wide Changes in Histone H3 Lysine 27 Trimethylation upon EZH2 Inhibition.\u003c/strong\u003e \u003cem\u003ePLoS One \u003c/em\u003e2016, \u003cstrong\u003e11:\u003c/strong\u003ee0166438.\u003c/li\u003e\n\u003cli\u003eRamirez F, Ryan DP, Gruning B, Bhardwaj V, Kilpert F, Richter AS, Heyne S, Dundar F, Manke T: \u003cstrong\u003edeepTools2: a next generation web server for deep-sequencing data analysis.\u003c/strong\u003e \u003cem\u003eNucleic Acids Res \u003c/em\u003e2016, \u003cstrong\u003e44:\u003c/strong\u003eW160-165.\u003c/li\u003e\n\u003cli\u003eZhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, Liu XS: \u003cstrong\u003eModel-based analysis of ChIP-Seq (MACS).\u003c/strong\u003e \u003cem\u003eGenome Biol \u003c/em\u003e2008, \u003cstrong\u003e9:\u003c/strong\u003eR137.\u003c/li\u003e\n\u003cli\u003eGerstein MB, Lu ZJ, Van Nostrand EL, Cheng C, Arshinoff BI, Liu T, Yip KY, Robilotto R, Rechtsteiner A, Ikegami K, et al: \u003cstrong\u003eIntegrative analysis of the Caenorhabditis elegans genome by the modENCODE project.\u003c/strong\u003e \u003cem\u003eScience \u003c/em\u003e2010, \u003cstrong\u003e330:\u003c/strong\u003e1775-1787.\u003c/li\u003e\n\u003cli\u003eChen RA, Down TA, Stempor P, Chen QB, Egelhofer TA, Hillier LW, Jeffers TE, Ahringer J: \u003cstrong\u003eThe landscape of RNA polymerase II transcription initiation in C. elegans reveals promoter and enhancer architectures.\u003c/strong\u003e \u003cem\u003eGenome Res \u003c/em\u003e2013, \u003cstrong\u003e23:\u003c/strong\u003e1339-1347.\u003c/li\u003e\n\u003cli\u003eJanes J, Dong Y, Schoof M, Serizay J, Appert A, Cerrato C, Woodbury C, Chen R, Gemma C, Huang N, et al: \u003cstrong\u003eChromatin accessibility dynamics across C. elegans development and ageing.\u003c/strong\u003e \u003cem\u003eElife \u003c/em\u003e2018, \u003cstrong\u003e7\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eBolger AM, Lohse M, Usadel B: \u003cstrong\u003eTrimmomatic: a flexible trimmer for Illumina sequence data.\u003c/strong\u003e \u003cem\u003eBioinformatics \u003c/em\u003e2014, \u003cstrong\u003e30:\u003c/strong\u003e2114-2120.\u003c/li\u003e\n\u003cli\u003eKim D, Pertea G, Trapnell C, Pimentel H, Kelley R, Salzberg SL: \u003cstrong\u003eTopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions.\u003c/strong\u003e \u003cem\u003eGenome Biol \u003c/em\u003e2013, \u003cstrong\u003e14:\u003c/strong\u003eR36.\u003c/li\u003e\n\u003cli\u003eAnders S, Pyl PT, Huber W: \u003cstrong\u003eHTSeq--a Python framework to work with high-throughput sequencing data.\u003c/strong\u003e \u003cem\u003eBioinformatics \u003c/em\u003e2015, \u003cstrong\u003e31:\u003c/strong\u003e166-169.\u003c/li\u003e\n\u003cli\u003eLove MI, Huber W, Anders S: \u003cstrong\u003eModerated estimation of fold change and dispersion for RNA-seq data with DESeq2.\u003c/strong\u003e \u003cem\u003eGenome Biol \u003c/em\u003e2014, \u003cstrong\u003e15:\u003c/strong\u003e550.\u003c/li\u003e\n\u003cli\u003eOrlando DA, Chen MW, Brown VE, Solanki S, Choi YJ, Olson ER, Fritz CC, Bradner JE, Guenther MG: \u003cstrong\u003eQuantitative ChIP-Seq normalization reveals global modulation of the epigenome.\u003c/strong\u003e \u003cem\u003eCell Rep \u003c/em\u003e2014, \u003cstrong\u003e9:\u003c/strong\u003e1163-1170.\u003c/li\u003e\n\u003cli\u003eHoldorf AD, Higgins DP, Hart AC, Boag PR, Pazour GJ, Walhout AJM, Walker AK: \u003cstrong\u003eWormCat: An Online Tool for Annotation and Visualization of Caenorhabditis elegans Genome-Scale Data.\u003c/strong\u003e \u003cem\u003eGenetics \u003c/em\u003e2020, \u003cstrong\u003e214:\u003c/strong\u003e279-294.\u003c/li\u003e\n\u003cli\u003eAyoub A, Park SH, Lee YT, Cho US, Dou Y: \u003cstrong\u003eRegulation of MLL1 Methyltransferase Activity in Two Distinct Nucleosome Binding Modes.\u003c/strong\u003e \u003cem\u003eBiochemistry \u003c/em\u003e2022, \u003cstrong\u003e61:\u003c/strong\u003e1-9.\u003c/li\u003e\n\u003cli\u003ePark SH, Ayoub A, Lee YT, Xu J, Kim H, Zheng W, Zhang B, Sha L, An S, Zhang Y, et al: \u003cstrong\u003eCryo-EM structure of the human MLL1 core complex bound to the nucleosome.\u003c/strong\u003e \u003cem\u003eNat Commun \u003c/em\u003e2019, \u003cstrong\u003e10:\u003c/strong\u003e5540.\u003c/li\u003e\n\u003cli\u003eMittal A, Hobor F, Zhang Y, Martin SR, Gamblin SJ, Ramos A, Wilson JR: \u003cstrong\u003eThe structure of the RbBP5 beta-propeller domain reveals a surface with potential nucleic acid binding sites.\u003c/strong\u003e \u003cem\u003eNucleic Acids Res \u003c/em\u003e2018, \u003cstrong\u003e46:\u003c/strong\u003e3802-3812.\u003c/li\u003e\n\u003cli\u003eXiao Y, Bedet C, Robert VJ, Simonet T, Dunkelbarger S, Rakotomalala C, Soete G, Korswagen HC, Strome S, Palladino F: \u003cstrong\u003eCaenorhabditis elegans chromatin-associated proteins SET-2 and ASH-2 are differentially required for histone H3 Lys 4 methylation in embryos and adult germ cells.\u003c/strong\u003e \u003cem\u003eProc Natl Acad Sci U S A \u003c/em\u003e2011, \u003cstrong\u003e108:\u003c/strong\u003e8305-8310.\u003c/li\u003e\n\u003cli\u003eWysocka J, Swigut T, Milne TA, Dou Y, Zhang X, Burlingame AL, Roeder RG, Brivanlou AH, Allis CD: \u003cstrong\u003eWDR5 associates with histone H3 methylated at K4 and is essential for H3 K4 methylation and vertebrate development.\u003c/strong\u003e \u003cem\u003eCell \u003c/em\u003e2005, \u003cstrong\u003e121:\u003c/strong\u003e859-872.\u003c/li\u003e\n\u003cli\u003eFischer V, Plassard D, Ye T, Reina-San-Martin B, Stierle M, Tora L, Devys D: \u003cstrong\u003eThe related coactivator complexes SAGA and ATAC control embryonic stem cell self-renewal through acetyltransferase-independent mechanisms.\u003c/strong\u003e \u003cem\u003eCell Rep \u003c/em\u003e2021, \u003cstrong\u003e36:\u003c/strong\u003e109598.\u003c/li\u003e\n\u003cli\u003eShi X, Hong T, Walter KL, Ewalt M, Michishita E, Hung T, Carney D, Pena P, Lan F, Kaadige MR, et al: \u003cstrong\u003eING2 PHD domain links histone H3 lysine 4 methylation to active gene repression.\u003c/strong\u003e \u003cem\u003eNature \u003c/em\u003e2006, \u003cstrong\u003e442:\u003c/strong\u003e96-99.\u003c/li\u003e\n\u003cli\u003eLi Q, Huang Y, Xu J, Mao F, Zhou B, Sun L, Basinski BW, Aksu M, Liu J, Dou Y, Rao RC: \u003cstrong\u003ep53 inactivation unmasks histone methylation-independent WDR5 functions that drive self-renewal and differentiation of pluripotent stem cells.\u003c/strong\u003e \u003cem\u003eStem Cell Reports \u003c/em\u003e2021, \u003cstrong\u003e16:\u003c/strong\u003e2642-2658.\u003c/li\u003e\n\u003cli\u003eKulkarni SS, Khokha MK: \u003cstrong\u003eWDR5 regulates left-right patterning via chromatin-dependent and -independent functions.\u003c/strong\u003e \u003cem\u003eDevelopment \u003c/em\u003e2018, \u003cstrong\u003e145\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eLi T, Kelly WG: \u003cstrong\u003eA role for WDR5 in TRA-1/Gli mediated transcriptional control of the sperm/oocyte switch in C. elegans.\u003c/strong\u003e \u003cem\u003eNucleic Acids Res \u003c/em\u003e2014, \u003cstrong\u003e42:\u003c/strong\u003e5567-5581.\u003c/li\u003e\n\u003cli\u003eHuang Y, Jay KL, Huang AY, Wan J, Jangam SV, Chorin O, Rothschild A, Barel O, Mariani M, Iascone M, et al: \u003cstrong\u003eLoss-of-function in RBBP5 results in a syndromic neurodevelopmental disorder associated with microcephaly.\u003c/strong\u003e \u003cem\u003eGenet Med \u003c/em\u003e2024\u003cstrong\u003e:\u003c/strong\u003e101218.\u003c/li\u003e\n\u003cli\u003eKamath RS, Fraser AG, Dong Y, Poulin G, Durbin R, Gotta M, Kanapin A, Le Bot N, Moreno S, Sohrmann M, et al: \u003cstrong\u003eSystematic functional analysis of the Caenorhabditis elegans genome using RNAi.\u003c/strong\u003e \u003cem\u003eNature \u003c/em\u003e2003, \u003cstrong\u003e421:\u003c/strong\u003e231-237.\u003c/li\u003e\n\u003cli\u003eMazzetto M, Gonzalez LE, Sanchez N, Reinke V: \u003cstrong\u003eCharacterization of the distribution and dynamics of chromatin states in the C. elegans germline reveals substantial H3K4me3 remodeling during oogenesis.\u003c/strong\u003e \u003cem\u003eGenome Res \u003c/em\u003e2024, \u003cstrong\u003e34:\u003c/strong\u003e57-69.\u003c/li\u003e\n\u003cli\u003eZylicz JJ, Bousard A, Zumer K, Dossin F, Mohammad E, da Rocha ST, Schwalb B, Syx L, Dingli F, Loew D, et al: \u003cstrong\u003eThe Implication of Early Chromatin Changes in X Chromosome Inactivation.\u003c/strong\u003e \u003cem\u003eCell \u003c/em\u003e2019, \u003cstrong\u003e176:\u003c/strong\u003e182-197 e123.\u003c/li\u003e\n\u003cli\u003ePferdehirt RR, Kruesi WS, Meyer BJ: \u003cstrong\u003eAn MLL/COMPASS subunit functions in the C. elegans dosage compensation complex to target X chromosomes for transcriptional regulation of gene expression.\u003c/strong\u003e \u003cem\u003eGenes Dev \u003c/em\u003e2011, \u003cstrong\u003e25:\u003c/strong\u003e499-515.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"epigenetics-and-chromatin","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"epch","sideBox":"Learn more about [Epigenetics \u0026 Chromatin](http://epigeneticsandchromatin.biomedcentral.com/)","snPcode":"13072","submissionUrl":"https://submission.nature.com/new-submission/13072/3","title":"Epigenetics \u0026 Chromatin","twitterHandle":"@EpigenChromatin","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Chromatin, H3K4 methylation, MLL/SET/COMPASS complex, chromosome X, WDR-5, RBBP-5, C. elegans embryo","lastPublishedDoi":"10.21203/rs.3.rs-7240678/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7240678/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eHistone H3 lysine 4 methylation (H3K4me) is generally associated with active transcription and bivalent chromatin, but can also contribute to repression. In metazoans, H3K4 methylation is catalysed by KMT2 methyltransferases assembled with the core scaffolding proteins WDR5, ASH2L, and RBBP5. RBBP5 mediates complex assembly and nucleosome binding, whilst WDR5 stabilises interactions to promote tri-methylation. However, WDR5 also exhibits additional \u0026lsquo;moonlighting\u0026rsquo; functions, leaving its specific roles in H3K4 methylation and transcription regulation unclear. Using \u003cem\u003eC. elegans\u003c/em\u003e embryos, spike-in ChIP-seq, and null alleles of \u003cem\u003ewdr-5(-)\u003c/em\u003e and \u003cem\u003erbbp-5(-)\u003c/em\u003e, we dissected the contributions of these scaffolds towards H3K4 mono-, di-, and tri-methylation as well as gene expression during \u003cem\u003eC. elegans\u003c/em\u003e embryogenesis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eWe show that \u003cem\u003eC. elegans\u003c/em\u003e RBBP-5 is essential for both mono- and multi-methylated H3K4 deposition. On the other hand, WDR-5 is primarily required for H3K4me3, but can influence H3K4me2 and H3K4me1 deposition either positively or negatively depending on the genomic feature involved. We additionally performed RNA-seq on these mutants and found that \u003cem\u003erbbp-5\u003c/em\u003e deletion was largely tolerated with mis-regulation of ~\u0026thinsp;700 genes, whereas the \u003cem\u003ewdr-5\u003c/em\u003e deletion led to widespread transcriptomic disruption (~\u0026thinsp;3000 genes). We initially hypothesised that these broad changes were driven by the altered H3K4me1 and H3K4me2 landscapes in the \u003cem\u003ewdr-5(-)\u003c/em\u003e mutant. However, transcriptomic profiling of the \u003cem\u003ewdr-5(-); rbbp-5(-)\u003c/em\u003e double mutant, which lacks H3K4 methylation, revealed a high degree of similarity to the \u003cem\u003ewdr-5(-)\u003c/em\u003e single mutant. This refuted our initial hypothesis and indicates that the changes in H3K4 methylation are unlikely to underlie the transcriptional effects of the \u003cem\u003ewdr-5\u003c/em\u003e deletion.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eOur findings strongly indicate that WDR-5 profoundly shapes gene expression through mechanisms beyond H3K4 methylation. Distinguishing between H3K4me-dependent and independent functions of WDR-5 will further understanding of its roles in development and disease.\u003c/p\u003e","manuscriptTitle":"WDR-5 exhibits H3K4 methylation-independent activity during embryonic development in C. elegans","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-04 16:19:50","doi":"10.21203/rs.3.rs-7240678/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-18T10:01:01+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-18T09:16:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-13T14:13:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-08T02:52:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"38659942402909654205387557589023022185","date":"2025-08-06T15:13:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"187443638101264489891006253568473447835","date":"2025-08-06T08:49:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"31779985958542224990347725132502763945","date":"2025-07-31T14:14:01+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-30T17:12:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-30T17:10:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-30T07:25:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"Epigenetics \u0026 Chromatin","date":"2025-07-29T08:00:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"epigenetics-and-chromatin","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"epch","sideBox":"Learn more about [Epigenetics \u0026 Chromatin](http://epigeneticsandchromatin.biomedcentral.com/)","snPcode":"13072","submissionUrl":"https://submission.nature.com/new-submission/13072/3","title":"Epigenetics \u0026 Chromatin","twitterHandle":"@EpigenChromatin","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fa875608-82e8-4098-9e5e-a874900b522f","owner":[],"postedDate":"August 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T16:19:16+00:00","versionOfRecord":{"articleIdentity":"rs-7240678","link":"https://doi.org/10.1186/s13072-026-00669-y","journal":{"identity":"epigenetics-and-chromatin","isVorOnly":false,"title":"Epigenetics \u0026 Chromatin"},"publishedOn":"2026-03-25 16:11:42","publishedOnDateReadable":"March 25th, 2026"},"versionCreatedAt":"2025-08-04 16:19:50","video":"","vorDoi":"10.1186/s13072-026-00669-y","vorDoiUrl":"https://doi.org/10.1186/s13072-026-00669-y","workflowStages":[]},"version":"v1","identity":"rs-7240678","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7240678","identity":"rs-7240678","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}